","Numerical Question","2","5",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.6",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.6",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","100",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.2",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","100",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","100",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.4",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.6",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.5",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.4",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.8",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.5",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","5",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.8",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","15",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.4",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.8",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","5",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.5",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.8",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.1",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.4",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","2",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1.2",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.5",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","10",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.6",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","100",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine natural frequency (omega n - ω_{n}), in rad/second, ","Determine the natural frequency (omega n - ω_{n}), in rad/second, of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.8",""," ", "//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping ratio (zeta - ζ) ","Determine the damping ratio (zeta - ζ) of a system from analysis of its differential equation, given below.

","Numerical Question","2","0.6",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match a system's impulse response to its differential equation","Match the system's impulse response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E:

1. undamped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. undamped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled C: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled C- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. undamped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled E: 1. undamped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D- Note: zeta = 1: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled B: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled A: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. undamped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled C: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

1. under damped

2. critically damped ** 3. over damped.**

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled C: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled C: 1. under damped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Determine damping type","Is the waveform labelled D: 1. undamped 2. critically damped **

** Enter 1, 2 or 3 in the answer field. **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Continuous systems and their representations/time-domain","continuous_system_time_domain","Match the system's step to its differential equation","Match the system's step response to its differential equation","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.141 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.923 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.7096 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.1487 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.5768 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7168 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7607 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.8541 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.922 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.5914 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.3",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.3014 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.0625 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.037 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.0737 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.287 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.9775 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.4933 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.1597 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.6126 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.179 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.863 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.3987 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8858 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.048 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7877 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.6381 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.605 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.6297 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.6462 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.2923 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.9819 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.5757 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.0034 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7606 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3479 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.5817 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.597 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.8894 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3082 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.3483 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.0038 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.1445 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.3",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3847 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.6263 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.5531 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.0142 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.4604 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.6682 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8666 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3281 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.3421 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.7927 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.4211 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.4758 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.0494 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.2109 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.9797 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.9752 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.2637 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.1022 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.3",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.4135 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8778 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8415 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.423 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.2",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.237 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.224 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.239 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.0721 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7979 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.9488 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.4555 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.1196 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.5823 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8296 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.5426 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.3",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.0225 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.2004 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.9733 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.7587 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.6",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.1861 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.8129 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.9",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8467 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.0713 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.6319 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.2574 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.3",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.9844 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.324 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.5051 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","3.5",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.7465 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","2.8",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.774 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3753 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.4",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=1.164 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.1",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.0629 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.7",""," ",
"//Signals and systems/Correlation","discrete_correlation","Quasi-Periodic Analysis - Determine Local Period","A time-domain signal is contained the zip file located at signal.zip , and has been corrupted with broadband noise . **

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.9875 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.2824 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.9992 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.1968 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=0.8358 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.4108 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local period of the signal varies from 2.5 milliseconds to 10 milliseconds. Determine the local period, in milliseconds (within 2% tolerance), of this signal at time t=2.3617 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","4.3",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 129Hz and of length 97 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","1.3299",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 435Hz and of length 55 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7.9091",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 593Hz and of length 21 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","28.2381",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 758Hz and of length 33 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","22.9697",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 699Hz and of length 59 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","11.8475",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 811Hz and of length 83 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","9.7711",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 398Hz and of length 16 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","24.875",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 922Hz and of length 79 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","11.6709",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 691Hz and of length 58 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","11.9138",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 306Hz and of length 70 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","4.3714",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 885Hz and of length 69 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","12.8261",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 832Hz and of length 53 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","15.6981",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 321Hz and of length 70 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","4.5857",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 42Hz and of length 74 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","0.56757",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 731Hz and of length 95 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7.6947",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 212Hz and of length 40 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","5.3",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 128Hz and of length 88 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","1.4545",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 199Hz and of length 42 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","4.7381",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 321Hz and of length 59 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","5.4407",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 271Hz and of length 32 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","8.4688",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 591Hz and of length 33 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","17.9091",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 715Hz and of length 70 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","10.2143",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 871Hz and of length 85 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","10.2471",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 247Hz and of length 62 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","3.9839",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 647Hz and of length 10 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","64.7",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 671Hz and of length 97 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","6.9175",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 446Hz and of length 104 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","4.2885",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 789Hz and of length 64 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","12.3281",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 730Hz and of length 98 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7.449",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 337Hz and of length 98 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","3.4388",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 766Hz and of length 101 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7.5842",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 298Hz and of length 48 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","6.2083",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 335Hz and of length 10 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","33.5",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 626Hz and of length 43 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","14.5581",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 623Hz and of length 89 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 765Hz and of length 83 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","9.2169",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 40Hz and of length 22 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","1.8182",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 154Hz and of length 36 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","4.2778",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 548Hz and of length 60 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","9.1333",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 571Hz and of length 21 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","27.1905",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 530Hz and of length 45 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","11.7778",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 245Hz and of length 66 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","3.7121",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 224Hz and of length 25 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","8.96",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 79Hz and of length 75 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","1.0533",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 793Hz and of length 56 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","14.1607",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 675Hz and of length 85 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","7.9412",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 674Hz and of length 14 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","48.1429",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 181Hz and of length 19 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","9.5263",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 276Hz and of length 54 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","5.1111",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 822Hz and of length 68 samples, what is the frequency resolution of the magnitude spectrum in Hertz? In other words what is the separation between frequency bins in Hertz? **

**","Numerical Question","1","12.0882",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","16.1031",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","9.1436",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","11.0125",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","8.4235",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.1684",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","4.2566",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","14.3945",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","14.3497",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","7.9595",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","16.2166",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","10.5933",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","9.0118",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","8.4803",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.8844",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","11.9456",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","8.6389",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","5.7531",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","4.2129",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.9584",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","9.5127",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","12.3424",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","5.2226",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","12.6458",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","2.3321",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","11.8459",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","14.4019",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","2.139",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","6.5226",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","11.4498",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","15.6747",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","7.0278",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","2.8062",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","9.0212",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","3.0604",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","8.2363",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","15.4426",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","5.6755",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","5.9835",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.0168",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","4.7779",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","12.1615",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.5246",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","4.9736",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","2.0454",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","5.9531",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","4.7547",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","12.0622",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","13.6494",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","12.7122",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT fundamentals","DFT_fundamentals","DFT Analysis of Plot","The plot in the figure below shows the magnitude frequency content of a sinusoidal signal x[n]. What is the amplitude of the sinusoidal signal?**

** **

**","Numerical Question","10","8.7228",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 114 Hz and of length 381 samples (download), contains two sinusoidal waveforms of frequencies 13 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","95",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 98 Hz and of length 638 samples (download), contains two sinusoidal waveforms of frequencies 14 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","123",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 155 Hz and of length 1344 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 24 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","259",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 164 Hz and of length 1313 samples (download), contains two sinusoidal waveforms of frequencies 22 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","274",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 113 Hz and of length 697 samples (download), contains two sinusoidal waveforms of frequencies 14 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","95",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 187 Hz and of length 873 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 27 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","156",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 113 Hz and of length 588 samples (download), contains two sinusoidal waveforms of frequencies 15 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","113",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 138 Hz and of length 829 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","173",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 96 Hz and of length 929 samples (download), contains two sinusoidal waveforms of frequencies 14 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","160",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 103 Hz and of length 722 samples (download), contains two sinusoidal waveforms of frequencies 13 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","103",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 139 Hz and of length 1808 samples (download), contains two sinusoidal waveforms of frequencies 22 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","232",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 146 Hz and of length 767 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","183",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 137 Hz and of length 1268 samples (download), contains two sinusoidal waveforms of frequencies 22 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","172",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 179 Hz and of length 1030 samples (download), contains two sinusoidal waveforms of frequencies 25 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","224",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 199 Hz and of length 1394 samples (download), contains two sinusoidal waveforms of frequencies 25 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","200",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 110 Hz and of length 807 samples (download), contains two sinusoidal waveforms of frequencies 17 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","184",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 93 Hz and of length 1086 samples (download), contains two sinusoidal waveforms of frequencies 13 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","155",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 111 Hz and of length 593 samples (download), contains two sinusoidal waveforms of frequencies 16 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","93",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 184 Hz and of length 1074 samples (download), contains two sinusoidal waveforms of frequencies 28 Hz and 34 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","154",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 123 Hz and of length 886 samples (download), contains two sinusoidal waveforms of frequencies 18 Hz and 23 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","123",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 168 Hz and of length 2185 samples (download), contains two sinusoidal waveforms of frequencies 26 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","280",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 202 Hz and of length 1482 samples (download), contains two sinusoidal waveforms of frequencies 26 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","337",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 127 Hz and of length 1271 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 24 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","212",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 136 Hz and of length 1043 samples (download), contains two sinusoidal waveforms of frequencies 18 Hz and 21 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","227",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 117 Hz and of length 609 samples (download), contains two sinusoidal waveforms of frequencies 15 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","118",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 104 Hz and of length 1145 samples (download), contains two sinusoidal waveforms of frequencies 14 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","174",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 188 Hz and of length 1392 samples (download), contains two sinusoidal waveforms of frequencies 24 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","188",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 112 Hz and of length 897 samples (download), contains two sinusoidal waveforms of frequencies 16 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","140",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 184 Hz and of length 890 samples (download), contains two sinusoidal waveforms of frequencies 29 Hz and 35 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","154",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 205 Hz and of length 821 samples (download), contains two sinusoidal waveforms of frequencies 27 Hz and 33 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","171",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 160 Hz and of length 865 samples (download), contains two sinusoidal waveforms of frequencies 20 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","160",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 190 Hz and of length 1445 samples (download), contains two sinusoidal waveforms of frequencies 23 Hz and 28 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","190",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 105 Hz and of length 631 samples (download), contains two sinusoidal waveforms of frequencies 13 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","132",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 122 Hz and of length 1099 samples (download), contains two sinusoidal waveforms of frequencies 15 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","153",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 147 Hz and of length 883 samples (download), contains two sinusoidal waveforms of frequencies 24 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","147",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 158 Hz and of length 554 samples (download), contains two sinusoidal waveforms of frequencies 25 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","132",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 181 Hz and of length 906 samples (download), contains two sinusoidal waveforms of frequencies 21 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","181",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 205 Hz and of length 1026 samples (download), contains two sinusoidal waveforms of frequencies 25 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","205",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 181 Hz and of length 1087 samples (download), contains two sinusoidal waveforms of frequencies 29 Hz and 33 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","227",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 192 Hz and of length 1498 samples (download), contains two sinusoidal waveforms of frequencies 26 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","193",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 169 Hz and of length 947 samples (download), contains two sinusoidal waveforms of frequencies 27 Hz and 32 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","170",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 108 Hz and of length 865 samples (download), contains two sinusoidal waveforms of frequencies 15 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","135",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 179 Hz and of length 1343 samples (download), contains two sinusoidal waveforms of frequencies 30 Hz and 34 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","224",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 169 Hz and of length 874 samples (download), contains two sinusoidal waveforms of frequencies 20 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","141",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 120 Hz and of length 461 samples (download), contains two sinusoidal waveforms of frequencies 12 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","100",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 199 Hz and of length 2322 samples (download), contains two sinusoidal waveforms of frequencies 27 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","332",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 76 Hz and of length 913 samples (download), contains two sinusoidal waveforms of frequencies 11 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","127",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 154 Hz and of length 1233 samples (download), contains two sinusoidal waveforms of frequencies 24 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","154",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 116 Hz and of length 561 samples (download), contains two sinusoidal waveforms of frequencies 16 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","97",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 136 Hz and of length 817 samples (download), contains two sinusoidal waveforms of frequencies 20 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","136",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 140 Hz and of length 1027 samples , contains two sinusoidal waveforms of frequencies 19 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","234",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 109 Hz and of length 736 samples , contains two sinusoidal waveforms of frequencies 12 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","137",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 190 Hz and of length 1521 samples , contains two sinusoidal waveforms of frequencies 29 Hz and 32 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","317",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 118 Hz and of length 1181 samples , contains two sinusoidal waveforms of frequencies 16 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","197",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 201 Hz and of length 1508 samples , contains two sinusoidal waveforms of frequencies 29 Hz and 33 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","252",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 244 Hz and of length 895 samples , contains two sinusoidal waveforms of frequencies 29 Hz and 35 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","204",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 115 Hz and of length 484 samples , contains two sinusoidal waveforms of frequencies 18 Hz and 23 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","115",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 141 Hz and of length 1317 samples , contains two sinusoidal waveforms of frequencies 22 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","235",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 86 Hz and of length 431 samples , contains two sinusoidal waveforms of frequencies 12 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","86",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 130 Hz and of length 694 samples , contains two sinusoidal waveforms of frequencies 14 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","109",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 173 Hz and of length 762 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","173",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 220 Hz and of length 1027 samples , contains two sinusoidal waveforms of frequencies 30 Hz and 36 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","184",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 180 Hz and of length 811 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","150",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 98 Hz and of length 621 samples , contains two sinusoidal waveforms of frequencies 13 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","82",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 194 Hz and of length 1019 samples , contains two sinusoidal waveforms of frequencies 28 Hz and 32 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","243",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 177 Hz and of length 1638 samples , contains two sinusoidal waveforms of frequencies 27 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","222",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 194 Hz and of length 2393 samples , contains two sinusoidal waveforms of frequencies 30 Hz and 33 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","324",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 156 Hz and of length 1327 samples , contains two sinusoidal waveforms of frequencies 22 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","195",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 112 Hz and of length 1419 samples , contains two sinusoidal waveforms of frequencies 18 Hz and 21 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","187",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 189 Hz and of length 1954 samples , contains two sinusoidal waveforms of frequencies 27 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","315",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 140 Hz and of length 1214 samples , contains two sinusoidal waveforms of frequencies 17 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","234",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 175 Hz and of length 1051 samples , contains two sinusoidal waveforms of frequencies 20 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","146",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 165 Hz and of length 771 samples , contains two sinusoidal waveforms of frequencies 22 Hz and 28 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","138",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 127 Hz and of length 1017 samples , contains two sinusoidal waveforms of frequencies 14 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","128",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 137 Hz and of length 740 samples , contains two sinusoidal waveforms of frequencies 17 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","137",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 137 Hz and of length 1188 samples , contains two sinusoidal waveforms of frequencies 23 Hz and 26 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","229",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 135 Hz and of length 518 samples , contains two sinusoidal waveforms of frequencies 17 Hz and 23 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","113",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 132 Hz and of length 1277 samples , contains two sinusoidal waveforms of frequencies 19 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","220",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 85 Hz and of length 879 samples , contains two sinusoidal waveforms of frequencies 13 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","142",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 126 Hz and of length 1135 samples , contains two sinusoidal waveforms of frequencies 17 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","210",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 132 Hz and of length 1057 samples , contains two sinusoidal waveforms of frequencies 15 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","132",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 213 Hz and of length 782 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","178",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 146 Hz and of length 906 samples , contains two sinusoidal waveforms of frequencies 22 Hz and 27 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","146",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 193 Hz and of length 933 samples , contains two sinusoidal waveforms of frequencies 23 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","161",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 160 Hz and of length 1174 samples , contains two sinusoidal waveforms of frequencies 20 Hz and 23 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","267",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 178 Hz and of length 1113 samples , contains two sinusoidal waveforms of frequencies 29 Hz and 33 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","223",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 198 Hz and of length 1024 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 31 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","165",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 104 Hz and of length 1249 samples , contains two sinusoidal waveforms of frequencies 17 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","174",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 192 Hz and of length 961 samples , contains two sinusoidal waveforms of frequencies 24 Hz and 29 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","193",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 118 Hz and of length 1495 samples , contains two sinusoidal waveforms of frequencies 14 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","197",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 119 Hz and of length 1587 samples , contains two sinusoidal waveforms of frequencies 18 Hz and 21 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","199",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 169 Hz and of length 1465 samples , contains two sinusoidal waveforms of frequencies 24 Hz and 27 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","282",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 168 Hz and of length 706 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","168",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 125 Hz and of length 605 samples , contains two sinusoidal waveforms of frequencies 14 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","105",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 144 Hz and of length 980 samples , contains two sinusoidal waveforms of frequencies 22 Hz and 27 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","144",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 171 Hz and of length 913 samples , contains two sinusoidal waveforms of frequencies 24 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","143",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 172 Hz and of length 2294 samples , contains two sinusoidal waveforms of frequencies 29 Hz and 32 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","287",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 146 Hz and of length 1424 samples , contains two sinusoidal waveforms of frequencies 18 Hz and 22 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","183",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 208 Hz and of length 1165 samples , contains two sinusoidal waveforms of frequencies 25 Hz and 30 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","208",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 154 Hz and of length 886 samples , contains two sinusoidal waveforms of frequencies 21 Hz and 25 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","193",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 98 Hz and of length 197 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","38",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 103 Hz and of length 191 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","40",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 91 Hz and of length 232 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","42",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 113 Hz and of length 283 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","41",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 84 Hz and of length 188 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","42",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 125 Hz and of length 358 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","45",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 103 Hz and of length 197 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","47",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 106 Hz and of length 221 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","41",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 93 Hz and of length 233 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 95 Hz and of length 329 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","44",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 82 Hz and of length 194 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","38",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 95 Hz and of length 286 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","37",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 87 Hz and of length 182 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","37",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 86 Hz and of length 223 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","36",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 104 Hz and of length 209 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","48",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 106 Hz and of length 251 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","49",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 107 Hz and of length 176 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 126 Hz and of length 253 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","45",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 103 Hz and of length 246 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","40",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 96 Hz and of length 289 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","48",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 107 Hz and of length 245 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 87 Hz and of length 175 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","37",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 92 Hz and of length 234 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","46",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 99 Hz and of length 255 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","50",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 79 Hz and of length 195 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","40",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 120 Hz and of length 181 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","43",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 86 Hz and of length 243 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","40",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 103 Hz and of length 181 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","43",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 136 Hz and of length 282 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","49",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 115 Hz and of length 280 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","42",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 93 Hz and of length 213 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","34",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 123 Hz and of length 370 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","48",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 92 Hz and of length 327 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","42",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 109 Hz and of length 248 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","50",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 92 Hz and of length 238 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 89 Hz and of length 187 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","41",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 125 Hz and of length 202 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 19 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","49",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 122 Hz and of length 323 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 18 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","44",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 90 Hz and of length 181 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 17 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","38",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 78 Hz and of length 163 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 95 Hz and of length 205 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","37",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 94 Hz and of length 283 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 15 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","43",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 86 Hz and of length 142 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","43",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 105 Hz and of length 201 samples (download), contains two sinusoidal waveforms of frequencies 5 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","48",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 87 Hz and of length 241 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","34",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 101 Hz and of length 187 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 83 Hz and of length 160 samples (download), contains two sinusoidal waveforms of frequencies 4 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","35",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 130 Hz and of length 233 samples (download), contains two sinusoidal waveforms of frequencies 6 Hz and 20 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","47",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 97 Hz and of length 318 samples (download), contains two sinusoidal waveforms of frequencies 3 Hz and 14 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","45",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length","A time-domain discrete signal, sampled at 110 Hz and of length 205 samples (download), contains two sinusoidal waveforms of frequencies 2 Hz and 16 Hz. What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment, after being multiplied by a Hanning window, will clearly show the two sinusoids present such that the main lobes do not overlap. As can be seen in the figure any significant spectral energy associated with each of the two sinusoids is clearly separated by low spectral energy.**

** **

**Enter the length of the minimum length segment in samples in the answer field below. **

**. ","Numerical Question","3","55",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 317 Hz and of length 363 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 162 Hz and of length 314 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 181 Hz and of length 295 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 211 Hz and of length 328 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 245 Hz and of length 299 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 195 Hz and of length 310 samples (download), contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 161 Hz and of length 232 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 307 Hz and of length 260 samples (download), contains a sinusoidal waveform of frequency 26 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 205 Hz and of length 319 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 206 Hz and of length 237 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 239 Hz and of length 406 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 230 Hz and of length 361 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","10",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 321 Hz and of length 262 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 145 Hz and of length 413 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 314 Hz and of length 217 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 183 Hz and of length 286 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 193 Hz and of length 344 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 317 Hz and of length 307 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 172 Hz and of length 287 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 219 Hz and of length 366 samples (download), contains a sinusoidal waveform of frequency 21 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 336 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 232 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 194 Hz and of length 423 samples (download), contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 201 Hz and of length 312 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 322 Hz and of length 258 samples (download), contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 127 Hz and of length 393 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 217 Hz and of length 389 samples (download), contains a sinusoidal waveform of frequency 19 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 148 Hz and of length 388 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 205 Hz and of length 399 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 124 Hz and of length 305 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 308 Hz and of length 297 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 328 Hz and of length 352 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 272 Hz and of length 381 samples (download), contains a sinusoidal waveform of frequency 25 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 274 Hz and of length 377 samples (download), contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 129 Hz and of length 399 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 225 Hz and of length 462 samples (download), contains a sinusoidal waveform of frequency 19 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 256 Hz and of length 406 samples (download), contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 299 Hz and of length 359 samples (download), contains a sinusoidal waveform of frequency 25 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 163 Hz and of length 257 samples (download), contains a sinusoidal waveform of frequency 14 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 234 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 180 Hz and of length 259 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 172 Hz and of length 377 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 241 Hz and of length 285 samples (download), contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 180 Hz and of length 373 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 145 Hz and of length 268 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 308 Hz and of length 255 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 267 Hz and of length 291 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 251 Hz and of length 372 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 334 Hz and of length 424 samples (download), contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 280 Hz and of length 291 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 317 Hz and of length 363 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 162 Hz and of length 314 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 181 Hz and of length 295 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 211 Hz and of length 328 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 245 Hz and of length 299 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 195 Hz and of length 310 samples (download), contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 161 Hz and of length 232 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 307 Hz and of length 260 samples (download), contains a sinusoidal waveform of frequency 26 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 205 Hz and of length 319 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 206 Hz and of length 237 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 239 Hz and of length 406 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 230 Hz and of length 361 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","10",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 321 Hz and of length 262 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 145 Hz and of length 413 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 314 Hz and of length 217 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 183 Hz and of length 286 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 193 Hz and of length 344 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 317 Hz and of length 307 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 172 Hz and of length 287 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 219 Hz and of length 366 samples (download), contains a sinusoidal waveform of frequency 21 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 336 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 232 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 194 Hz and of length 423 samples (download), contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 201 Hz and of length 312 samples (download), contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 322 Hz and of length 258 samples (download), contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 127 Hz and of length 393 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 217 Hz and of length 389 samples (download), contains a sinusoidal waveform of frequency 19 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 148 Hz and of length 388 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 205 Hz and of length 399 samples (download), contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 124 Hz and of length 305 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 308 Hz and of length 297 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 328 Hz and of length 352 samples (download), contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 272 Hz and of length 381 samples (download), contains a sinusoidal waveform of frequency 25 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 274 Hz and of length 377 samples (download), contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 129 Hz and of length 399 samples (download), contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 225 Hz and of length 462 samples (download), contains a sinusoidal waveform of frequency 19 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 256 Hz and of length 406 samples (download), contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 299 Hz and of length 359 samples (download), contains a sinusoidal waveform of frequency 25 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 163 Hz and of length 257 samples (download), contains a sinusoidal waveform of frequency 14 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 295 Hz and of length 234 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 180 Hz and of length 259 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 172 Hz and of length 377 samples (download), contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 241 Hz and of length 285 samples (download), contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 180 Hz and of length 373 samples (download), contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 145 Hz and of length 268 samples (download), contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 308 Hz and of length 255 samples (download), contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 267 Hz and of length 291 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 251 Hz and of length 372 samples (download), contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 334 Hz and of length 424 samples (download), contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 280 Hz and of length 291 samples (download), contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 176 Hz and of length 404 samples , contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 305 Hz and of length 369 samples , contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 186 Hz and of length 269 samples , contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 155 Hz and of length 311 samples , contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 124 Hz and of length 269 samples , contains a sinusoidal waveform of frequency 12 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 302 Hz and of length 324 samples , contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 117 Hz and of length 341 samples , contains a sinusoidal waveform of frequency 11 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 191 Hz and of length 270 samples , contains a sinusoidal waveform of frequency 17 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 133 Hz and of length 311 samples , contains a sinusoidal waveform of frequency 12 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 181 Hz and of length 262 samples , contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 304 Hz and of length 396 samples , contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 248 Hz and of length 395 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 321 Hz and of length 396 samples , contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 278 Hz and of length 367 samples , contains a sinusoidal waveform of frequency 25 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 139 Hz and of length 290 samples , contains a sinusoidal waveform of frequency 12 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 262 Hz and of length 334 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 166 Hz and of length 270 samples , contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 198 Hz and of length 320 samples , contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 274 Hz and of length 446 samples , contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 253 Hz and of length 369 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 226 Hz and of length 362 samples , contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 278 Hz and of length 360 samples , contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 256 Hz and of length 268 samples , contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 224 Hz and of length 255 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 318 Hz and of length 319 samples , contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 246 Hz and of length 258 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 260 Hz and of length 441 samples , contains a sinusoidal waveform of frequency 23 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 337 Hz and of length 248 samples , contains a sinusoidal waveform of frequency 30 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 331 Hz and of length 354 samples , contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 268 Hz and of length 414 samples , contains a sinusoidal waveform of frequency 24 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 190 Hz and of length 307 samples , contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 267 Hz and of length 380 samples , contains a sinusoidal waveform of frequency 26 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 255 Hz and of length 383 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 131 Hz and of length 383 samples , contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 165 Hz and of length 448 samples , contains a sinusoidal waveform of frequency 14 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 162 Hz and of length 395 samples , contains a sinusoidal waveform of frequency 16 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 220 Hz and of length 441 samples , contains a sinusoidal waveform of frequency 19 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 307 Hz and of length 414 samples , contains a sinusoidal waveform of frequency 26 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 245 Hz and of length 379 samples , contains a sinusoidal waveform of frequency 22 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 138 Hz and of length 245 samples , contains a sinusoidal waveform of frequency 13 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 306 Hz and of length 416 samples , contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 166 Hz and of length 321 samples , contains a sinusoidal waveform of frequency 14 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 286 Hz and of length 348 samples , contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 224 Hz and of length 374 samples , contains a sinusoidal waveform of frequency 21 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 181 Hz and of length 252 samples , contains a sinusoidal waveform of frequency 18 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 237 Hz and of length 427 samples , contains a sinusoidal waveform of frequency 20 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 170 Hz and of length 261 samples , contains a sinusoidal waveform of frequency 15 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 292 Hz and of length 217 samples , contains a sinusoidal waveform of frequency 27 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 324 Hz and of length 347 samples , contains a sinusoidal waveform of frequency 29 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","12",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","DFT Window Length - Single Sinusoid","A time-domain discrete signal, sampled at 290 Hz and of length 373 samples , contains a sinusoidal waveform of frequency 28 Hz . What is the minimum length segment that could be extracted from this signal such that the magnitude spectrum of the extracted segment will clearly show the main lobe, as shown in the figure below.**

** **

**Enter the minimum length segment in samples in the answer field below. **

**.","Numerical Question","2","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.4629 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component (in fact this is more accurate to do this for this particular problem), however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions.**

**","Numerical Question","2","0.93537",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.0149 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component (in fact this is more accurate to do this for this particular problem), however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions.**

**","Numerical Question","2","1.0751",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=0.9786 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component (in fact this is more accurate to do this for this particular problem), however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions.**

**","Numerical Question","2","0.55814",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.3824 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.2869",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.3159 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.89012",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=0.9435 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.99151",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.8609 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.5964",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.1863 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.5506",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.1958 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1261",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.5603 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.81888",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.6278 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.91651",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.309 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.73783",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.3986 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.3166",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.5943 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.92139",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.545 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.76144",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.1513 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0079",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.2943 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.2555",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.3385 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.61211",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.0788 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.51426",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.3432 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.95859",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.0316 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.2564",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.4681 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0148",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.1505 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.94906",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.1387 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.165",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.4041 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.94617",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.3644 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.99282",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.2115 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0982",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.2657 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.98985",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.6585 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.3597",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.7613 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.40841",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.6979 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.40385",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.9441 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1379",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.0888 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.82843",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.7213 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0217",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=0.8787 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4487",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.6612 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.50697",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.8244 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.82697",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.2883 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0125",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=0.8091 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0537",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.9738 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1039",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.5954 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.56984",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.9987 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.46133",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.7865 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.62675",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.2603 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.61893",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.0296 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0815",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=0.8138 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.94703",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.4023 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.78046",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.5545 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.2169",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=2.5659 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.93267",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Amplitude","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude.**

**The amplitude of the quasi-sinusoidal signal is never less than 0.3. Determine the local amplitude of this signal at time t=1.9639 seconds (within 2% tolerance) where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.57132",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.194 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.68663",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.0393 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4591",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.1617 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1121",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.7477 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0109",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.5535 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.74062",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.6782 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.484",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.2674 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1767",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=0.9932 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.54108",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.2746 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.97594",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.3353 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4701",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.1857 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.99359",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.0715 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.3584",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.166 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.98439",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=0.8921 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.48824",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.9023 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.66904",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.3259 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1917",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.7226 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.83572",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.6747 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4378",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.7057 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.2679",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.3326 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.85508",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.1795 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0553",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.8724 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.86742",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.457 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.4242",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.5406 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.17",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.8968 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.59673",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.5575 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.8924",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.0234 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.98932",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.6197 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.1955",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.7817 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.77554",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.6996 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.99996",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.1297 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0336",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.8251 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4916",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.4788 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.4348",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.9749 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.4774",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=0.88 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.88052",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.5081 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.91488",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=0.9896 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.43321",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.1443 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0333",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.0467 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0697",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.4448 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.86426",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.8548 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.3064",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.7336 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0887",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.7574 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.71226",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.1878 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.83285",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.3032 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.7777",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.1198 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.5983",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=0.9001 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","0.47908",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.6673 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.0521",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=2.4093 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.4955",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Mulitple components","The time-domain signal contained in this zip file contains a number of quasi-sinusoidal signals which change slowly in both frequency and amplitude. The minimum amplitude quasi-sinusoidal signal is 0.3.**

** Determine the local amplitude (within 1.5% tolerance) of the lowest frequency component signal at time t=1.8916 where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","1.3482",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.799 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component, however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions which will follow.**

**","Numerical Question","2","263",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.8681 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component, however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions which will follow.**

**","Numerical Question","2","255",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.6086 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Note: you could answer this question by analysing the time-domain waveform to determine the local frequency of the quasi sinusoidal component, however if you can do this by analysing the DFT of the time-domain segment in the region of interest then you will be better positioned to answer more complex questions which will follow.**

**","Numerical Question","2","216",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.188 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","195",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.5513 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","245",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.6635 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","188",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.256 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","278",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.1185 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","264",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.8722 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","235",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.1002 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","267",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.3594 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","252",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.8746 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","285",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.4141 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","267",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.1353 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","294",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.046 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","265",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.4041 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","254",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.6972 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","265",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.0767 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","261",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.3026 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","253",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.912 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","256",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.2972 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","271",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.4655 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","271",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.314 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","262",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.8847 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","272",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.9237 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","273",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.057 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","279",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.8198 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","254",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.4711 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","204",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.2557 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","263",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.5628 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","281",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.6487 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","245",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.1118 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","263",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.4783 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","244",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.0324 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","254",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.9129 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","237",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.852 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","256",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.6407 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","286",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.8513 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.5625 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","268",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.8948 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","255",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.351 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","268",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.4508 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","285",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.9005 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","300",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.5967 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","260",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.0653 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","257",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=0.913 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","249",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.2361 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","257",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=2.0387 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","300",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.9011 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","255",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Quasi-Sinusoidal Analysis - Determine Frequency","The time-domain signal contained in this zip file is a quasi-sinusoidal signal which changes slowly in both frequency and amplitude. The amplitude of the quasi-sinusoidal signal is never less than 0.3.**

**Its local frequency varies from a min of 100 Hz to a max of 400 Hz. Determine the local frequency (within 2% tolerance) of this signal at time t=1.2339 seconds where t=0 corresponds to sample number 0 and the sampling frequency is 10000 Hz.**

**","Numerical Question","2","250",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 864Hz and of length 29 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 7.1405Hz? **

**","Numerical Question","1","92",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 643Hz and of length 44 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 8.2436Hz? **

**","Numerical Question","1","34",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 94Hz and of length 41 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 1.1059Hz? **

**","Numerical Question","1","44",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 805Hz and of length 81 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.9191Hz? **

**","Numerical Question","1","55",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 430Hz and of length 64 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 2.6875Hz? **

**","Numerical Question","1","96",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 18Hz and of length 57 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.25714Hz? **

**","Numerical Question","1","13",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 989Hz and of length 93 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.5562Hz? **

**","Numerical Question","1","85",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 658Hz and of length 71 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 4.2452Hz? **

**","Numerical Question","1","84",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 967Hz and of length 62 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 6.0062Hz? **

**","Numerical Question","1","99",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 838Hz and of length 19 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 27.9333Hz? **

**","Numerical Question","1","11",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 839Hz and of length 89 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 6.4046Hz? **

**","Numerical Question","1","42",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 475Hz and of length 18 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 9.3137Hz? **

**","Numerical Question","1","33",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 361Hz and of length 102 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 2.1488Hz? **

**","Numerical Question","1","66",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 315Hz and of length 21 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 7.5Hz? **

**","Numerical Question","1","21",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 788Hz and of length 64 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 6.2047Hz? **

**","Numerical Question","1","63",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 7Hz and of length 60 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.042169Hz? **

**","Numerical Question","1","106",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 465Hz and of length 25 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.407Hz? **

**","Numerical Question","1","61",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 801Hz and of length 38 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.4863Hz? **

**","Numerical Question","1","108",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 393Hz and of length 42 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 4.2717Hz? **

**","Numerical Question","1","50",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 615Hz and of length 78 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.2564Hz? **

**","Numerical Question","1","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 801Hz and of length 42 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 9.8889Hz? **

**","Numerical Question","1","39",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 554Hz and of length 78 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 4.541Hz? **

**","Numerical Question","1","44",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 811Hz and of length 63 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 10.5325Hz? **

**","Numerical Question","1","14",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 230Hz and of length 36 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 2.3Hz? **

**","Numerical Question","1","64",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 137Hz and of length 12 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 1.2124Hz? **

**","Numerical Question","1","101",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 237Hz and of length 89 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 1.529Hz? **

**","Numerical Question","1","66",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 130Hz and of length 96 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.68783Hz? **

**","Numerical Question","1","93",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 945Hz and of length 90 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 6.7021Hz? **

**","Numerical Question","1","51",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 497Hz and of length 46 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 3.381Hz? **

**","Numerical Question","1","101",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 662Hz and of length 37 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.1318Hz? **

**","Numerical Question","1","92",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 327Hz and of length 10 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 7.1087Hz? **

**","Numerical Question","1","36",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 30Hz and of length 27 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.56604Hz? **

**","Numerical Question","1","26",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 981Hz and of length 101 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 6.4967Hz? **

**","Numerical Question","1","50",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 542Hz and of length 88 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 2.7374Hz? **

**","Numerical Question","1","110",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 181Hz and of length 93 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 1.5877Hz? **

**","Numerical Question","1","21",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 663Hz and of length 30 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 14.1064Hz? **

**","Numerical Question","1","17",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 269Hz and of length 50 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 3.1279Hz? **

**","Numerical Question","1","36",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 551Hz and of length 104 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 2.6748Hz? **

**","Numerical Question","1","102",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 222Hz and of length 21 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 3.8276Hz? **

**","Numerical Question","1","37",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 552Hz and of length 92 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 3.1364Hz? **

**","Numerical Question","1","84",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 727Hz and of length 110 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 4.3018Hz? **

**","Numerical Question","1","59",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 980Hz and of length 91 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.6647Hz? **

**","Numerical Question","1","82",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 83Hz and of length 36 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.64844Hz? **

**","Numerical Question","1","92",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 175Hz and of length 103 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.89744Hz? **

**","Numerical Question","1","92",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 245Hz and of length 96 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 1.6554Hz? **

**","Numerical Question","1","52",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 61Hz and of length 20 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.488Hz? **

**","Numerical Question","1","105",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 574Hz and of length 32 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 5.5192Hz? **

**","Numerical Question","1","72",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 538Hz and of length 102 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 4.521Hz? **

**","Numerical Question","1","17",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 91Hz and of length 49 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 0.8835Hz? **

**","Numerical Question","1","54",""," ",
"//Signals and systems/Discrete Fourier Transform/DFT in practice","DFT_in_practice","Bin Frequency Resolution ","If you obtain the DFT of a time-domain discrete signal, sampled at 727Hz and of length 14 samples, how many zeros would you need to append to the signal in order to achieve a frequency resolution of 15.1458Hz? **

**","Numerical Question","1","34",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been fed into the system togther with the magnitude frequency response of the system.**

**The frequency content of the ouput of the system is shown in one of the four plots shown below, labelled 1, 2, 3, 4. Which plot is the frequency content of the system ouput? Enter 1, 2, 3, or 4 in the answer field.**

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been passed through the system togther with the magnitude frequency response of the system.**

**The frequency content of the ouput of the system is shown in one of the four plots shown below, labelled 1, 2, 3, 4. Which plot is the frequency content of the system ouput? Enter 1, 2, 3, or 4 in the answer field.**

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been fed into the system togther with the magnitude frequency response of the system.**

**The frequency content of the ouput of the system is shown in one of the four plots shown below, labelled 1, 2, 3, 4. Which plot is the frequency content of the system ouput? Enter 1, 2, 3, or 4 in the answer field.**

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been applied to the system togther with the magnitude frequency response of the system.**

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been fed into the system togther with the magnitude frequency response of the system.**

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been applied to the system togther with the magnitude frequency response of the system.**

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been applied to the system togther with the magnitude frequency response of the system.**

**The plots below show the magnitude content of the signal which has been passed through the system togther with the magnitude frequency response of the system.**

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**The plots below show the magnitude content of the signal which has been passed through the system togther with the magnitude frequency response of the system.**

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","System Frequency Response","A signal has been passed though a system.**

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

**The plot below shows the magnitude content of the signal which has been the system. The system has an impulse response which can be downloaded from impulse_data.zip .**

** **

** **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

**The plot below shows the magnitude content of the signal which has been the system. The system has an impulse response which can be downloaded from impulse_data.zip .**

** **

** **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

**The plot below shows the magnitude content of the signal which has been the system. The system has an impulse response which can be downloaded from impulse_data.zip .**

** **

** **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","2",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

**","Numerical Question","1","4",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

** **

** **

** **

** **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

** **

** **

** **

** **

**","Numerical Question","1","3",""," ",
"//Signals and systems/Discrete systems and their representations/frequency-domain","discrete_system_frequency_domain","Determine System output given the input and impulse response","A signal has been passed though a system.**

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**","Numerical Question","1","1",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match signal flow diagram to transfer function","match_signal_flow_to_tf","Match each system's transfer function to its signal flow representation","Shown below are three system signal flow representations and three transfer functions. Match each signal flow representation to its corresponding transfer function.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match frequency response to signal flow diagram","match_H_to_sig_flow","Match each system's magnitude frequency response to its signal flow representation","Shown below are three system signal flow representations and three magnitude frequency responses. Match each signal flow representation to its corresponding magnitude frequency response.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to frequency response","match_pz_to_freq_resp","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.31123x[n-1] + 0.25x[n-2] + 0.47563y[n-1] - y[n-2]"," ","","y[n] = x[n] + 0.69119x[n-1] + 0.16x[n-2] - 0.53521y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.35612x[n-1] + 0.36x[n-2] - 0.83905y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.7431x[n-1] + 0.81x[n-2] + 1.2058y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] - 1.7548x[n-1] + 0.81x[n-2] + 0.58905y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] - 1.7969x[n-1] + 0.81x[n-2] + 0.17418y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.29293x[n-1] + 0.36x[n-2] - 1.3154y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 1.5644x[n-1] + 0.64x[n-2] - 1.4035y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 0.74068x[n-1] + 0.16x[n-2] - 0.42898y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.0016365x[n-1] + 0.64x[n-2] + 0.79992y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.95425x[n-1] + 0.25x[n-2] + 1.7833y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 1.5116x[n-1] + 0.64x[n-2] - 0.22377y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.6613x[n-1] + 0.81x[n-2] + 1.709y[n-1] - y[n-2]"," ","","y[n] = x[n] - 0.27195x[n-1] + 0.81x[n-2] - 0.92914y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 1.1032x[n-1] + 0.36x[n-2] - 0.49616y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.6239x[n-1] + 0.81x[n-2] + 1.7934y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 0.12572x[n-1] + 0.16x[n-2] - 0.549y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] + 0.39932x[n-1] + 0.16x[n-2] - 0.79951y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.37714x[n-1] + 0.81x[n-2] - 1.8647y[n-1] - y[n-2]"," ","","y[n] = x[n] - 0.36432x[n-1] + 0.64x[n-2] + 1.0303y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 1.6935x[n-1] + 0.81x[n-2] - 0.59807y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.1969x[n-1] + 0.36x[n-2] - 0.85032y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.2053x[n-1] + 0.49x[n-2] + 1.7408y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 1.1904x[n-1] + 0.49x[n-2] - 1.1829y[n-1] - 0.36y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.33446x[n-1] + 0.25x[n-2] - 0.46191y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.65765x[n-1] + 0.16x[n-2] + 0.16268y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 1.5895x[n-1] + 0.64x[n-2] - 0.56381y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.54506x[n-1] + 0.49x[n-2] - 0.010941y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.1304x[n-1] + x[n-2] + 0.53558y[n-1] - 1y[n-2]"," ","","y[n] = x[n] + 0.072155x[n-1] + 0.49x[n-2] + 0.58944y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.7306x[n-1] + x[n-2] - 1.2457y[n-1] - y[n-2]"," ","","y[n] = x[n] + 0.19812x[n-1] + 0.36x[n-2] + 0.7757y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.57008x[n-1] + x[n-2] + 0.59789y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.078x[n-1] + 0.49x[n-2] + 0.15004y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] + 1.3496x[n-1] + 0.81x[n-2] - 0.7476y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.14828x[n-1] + 0.16x[n-2] + 0.14118y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.1937x[n-1] + 0.36x[n-2] + 1.989y[n-1] - y[n-2]"," ","","y[n] = x[n] - 0.52363x[n-1] + 0.09x[n-2] - 0.87901y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] - 1.2301x[n-1] + 0.64x[n-2] - 0.33552y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.16136x[n-1] + 0.16x[n-2] + 0.24012y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.83368x[n-1] + 0.64x[n-2] + 0.99664y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] - 0.54902x[n-1] + 0.36x[n-2] - 0.87001y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.071139x[n-1] + 0.36x[n-2] + 0.75245y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 0.73615x[n-1] + 0.36x[n-2] - 1.3615y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] + 0.31102x[n-1] + 0.25x[n-2] - 0.35624y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.84935x[n-1] + 0.81x[n-2] + 1.1707y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 0.53433x[n-1] + 0.16x[n-2] + 0.51124y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.7629x[n-1] + 0.81x[n-2] + 0.76641y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.3674x[n-1] + 0.49x[n-2] + 1.5481y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 1.5993x[n-1] + 0.64x[n-2] - 0.97052y[n-1] - y[n-2]"," ","","y[n] = x[n] - 1.2923x[n-1] + 0.49x[n-2] + 1.7267y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.75396x[n-1] + 0.49x[n-2] - 1.3882y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 1.1536x[n-1] + 0.36x[n-2] - 1.5929y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 1.1973x[n-1] + 0.36x[n-2] + 0.58405y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.35271x[n-1] + 0.64x[n-2] + 0.79656y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] - 0.22102x[n-1] + 0.09x[n-2] + 1.6935y[n-1] - y[n-2]"," ","","y[n] = x[n] - 0.58263x[n-1] + 0.49x[n-2] - 0.059401y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.035x[n-1] + 0.49x[n-2] + 1.1978y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 1.7987x[n-1] + 0.81x[n-2] - 0.63915y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 0.76173x[n-1] + 0.36x[n-2] - 0.70816y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.40611x[n-1] + 0.25x[n-2] - 1.2293y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 0.12003x[n-1] + 0.49x[n-2] - 1.3846y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 0.69124x[n-1] + 0.49x[n-2] + 0.42387y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.92199x[n-1] + 0.36x[n-2] - 0.4808y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] - 0.25407x[n-1] + 0.16x[n-2] - 0.27545y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] + 0.36584x[n-1] + 0.36x[n-2] + 0.98973y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.54121x[n-1] + 0.49x[n-2] - 0.90202y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 0.74004x[n-1] + 0.36x[n-2] + 0.99936y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.001x[n-1] + 0.49x[n-2] - 1.3977y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.27922x[n-1] + 0.36x[n-2] - 0.71554y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.0815x[n-1] + 0.36x[n-2] + 0.51458y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] + 0.78314x[n-1] + 0.64x[n-2] - 0.60816y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.3808x[n-1] + x[n-2] + 0.96988y[n-1] - y[n-2]"," ","","y[n] = x[n] + 0.78798x[n-1] + 0.16x[n-2] - 1.7984y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 1.3066x[n-1] + 0.49x[n-2] + 0.053066y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.83395x[n-1] + 0.36x[n-2] + 1.5731y[n-1] - y[n-2]"," ","","y[n] = x[n] + 1.2894x[n-1] + 0.81x[n-2] - 0.57062y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 1.8599x[n-1] + x[n-2] - 0.50448y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.95255x[n-1] + 0.49x[n-2] + 0.69265y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] + 0.64154x[n-1] + 0.16x[n-2] - 1.7984y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 1.5109x[n-1] + 0.64x[n-2] - 1.3985y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.17039x[n-1] + 0.81x[n-2] - 0.46414y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 0.56033x[n-1] + 0.09x[n-2] - 0.97433y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 0.25791x[n-1] + 0.09x[n-2] - 0.27043y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.3409x[n-1] + 0.64x[n-2] + 0.35617y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 0.66768x[n-1] + 0.49x[n-2] - 0.29197y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 0.88752x[n-1] + 0.25x[n-2] + 0.08148y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.55148x[n-1] + 0.36x[n-2] - 1.702y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 0.9866x[n-1] + 0.25x[n-2] + 0.29776y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 1.1921x[n-1] + x[n-2] + 0.89057y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.3252x[n-1] + 0.64x[n-2] - 1.1192y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 0.59991x[n-1] + 0.09x[n-2] + 0.24521y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 1.4101x[n-1] + 0.81x[n-2] + 0.30455y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.0518x[n-1] + 0.36x[n-2] - 0.77726y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.78604x[n-1] + 0.16x[n-2] - 0.39626y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 1.3384x[n-1] + 0.81x[n-2] + 1.1967y[n-1] - 0.36y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.59945x[n-1] + 0.09x[n-2] + 0.6196y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.75566x[n-1] + 0.25x[n-2] + 0.51658y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.58678x[n-1] + 0.16x[n-2] - 0.59544y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.9911x[n-1] + 1x[n-2] - 1.1708y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] + 1.7938x[n-1] + 0.81x[n-2] + 0.11447y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.1523x[n-1] + x[n-2] - 0.97094y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.79914x[n-1] + 0.16x[n-2] - 1.4859y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 1.1959x[n-1] + 0.36x[n-2] - 0.74015y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] + 0.73626x[n-1] + 0.36x[n-2] + 0.77711y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.96052x[n-1] + 0.36x[n-2] - 0.26544y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.22266x[n-1] + 0.49x[n-2] - 0.29014y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] - 0.36836x[n-1] + 0.49x[n-2] + 1.788y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.2765x[n-1] + 0.64x[n-2] - 1.3973y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 0.66809x[n-1] + 0.25x[n-2] + 0.11899y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.1072x[n-1] + 0.36x[n-2] + 0.51124y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 1.1152x[n-1] + 1x[n-2] - 1.262y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] - 0.3164x[n-1] + 0.16x[n-2] + 0.47948y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 1.9997x[n-1] + x[n-2] - 1.3261y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.42993x[n-1] + 0.16x[n-2] + 0.18779y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] - 0.25849x[n-1] + 0.09x[n-2] - 1.3127y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] + 0.37098x[n-1] + 0.64x[n-2] + 1.1955y[n-1] - 0.36y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.7728x[n-1] + 0.81x[n-2] - 0.88462y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 0.52615x[n-1] + 0.81x[n-2] - 0.55847y[n-1] - 0.25y[n-2]"," ","","y[n] = x[n] + 1.1137x[n-1] + 0.49x[n-2] + 1.5437y[n-1] - 0.64y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.88883x[n-1] + 0.49x[n-2] + 1.1914y[n-1] - y[n-2]"," ","","y[n] = x[n] - 0.41861x[n-1] + 0.81x[n-2] - 0.4737y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 0.47892x[n-1] + 0.09x[n-2] - 0.17417y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.82623x[n-1] + 0.49x[n-2] - 0.21706y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 1.1963x[n-1] + 0.36x[n-2] + 0.79915y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] + 1.3864x[n-1] + x[n-2] + 0.80906y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.27895x[n-1] + 0.09x[n-2] + 0.77463y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] + 0.93568x[n-1] + 0.36x[n-2] + 0.78178y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] - 1.1182x[n-1] + 0.36x[n-2] - 0.39983y[n-1] - 0.16y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.1375x[n-1] + 0.64x[n-2] + 0.54683y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 0.45058x[n-1] + 0.16x[n-2] - 1.339y[n-1] - 0.64y[n-2]"," ","","y[n] = x[n] + 0.22645x[n-1] + 0.09x[n-2] + 0.42327y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.82197x[n-1] + 0.81x[n-2] - 0.68473y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 1.6758x[n-1] + 0.81x[n-2] - 1.1592y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 1.5287x[n-1] + 0.64x[n-2] + 0.59672y[n-1] - 0.09y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.98821x[n-1] + 0.25x[n-2] + 0.51857y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] - 0.17249x[n-1] + 0.81x[n-2] + 1.028y[n-1] - 0.36y[n-2]"," ","","y[n] = x[n] - 1.5893x[n-1] + 0.64x[n-2] - 1.7926y[n-1] - 0.81y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.5844x[n-1] + 0.81x[n-2] - 1.6524y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 0.51149x[n-1] + 0.81x[n-2] - 0.65622y[n-1] - y[n-2]"," ","","y[n] = x[n] + 0.53532x[n-1] + 0.36x[n-2] - 0.67539y[n-1] - 0.25y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] - 0.10181x[n-1] + 0.09x[n-2] - 0.78724y[n-1] - 0.16y[n-2]"," ","","y[n] = x[n] + 0.7008x[n-1] + 0.49x[n-2] + 0.38229y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] + 1.598x[n-1] + 0.64x[n-2] - 0.79247y[n-1] - 0.49y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 1.367x[n-1] + 0.49x[n-2] - 1.5437y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] - 0.53925x[n-1] + 0.36x[n-2] + 0.4048y[n-1] - 0.09y[n-2]"," ","","y[n] = x[n] - 0.57423x[n-1] + 0.25x[n-2] - 0.18914y[n-1] - 0.36y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to difference equation","match_pz_to_diff_equ","Match each system's pole zero plot to its difference equation","Shown below are three system difference equations and three pole zero plots. Match each difference equation to its corresponding pole zero plot.","Matching Question","0","","y[n] = x[n] + 0.67225x[n-1] + 0.64x[n-2] - 1.511y[n-1] - 0.81y[n-2]"," ","","y[n] = x[n] + 1.2263x[n-1] + x[n-2] + 0.23351y[n-1] - 0.49y[n-2]"," ","","y[n] = x[n] + 0.3536x[n-1] + 0.64x[n-2] + 0.62639y[n-1] - 0.36y[n-2]"," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match pole-zero plot to signal flow diagram","match_pz_to_sig_flow","Match each system's pole zero plot to its signal flow representation","Shown below are three system signal flow representations and three pole zero plots. Match each signal flow representation to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","",""," ","",""," ","",""," ",
"//Signals and systems/Discrete systems and their representations/mixed system views/match resonator pole-zero plot to frequency response","match_pole_res_to_H","Match each system's pole zero plot to its magnitude frequency response","Shown below are three system magnitude frequency responses and three pole zero plots. Match each magnitude frequency response to its corresponding pole zero plot.","Matching Question","0","","**