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Worksheets21EC5252_DSP_Unit 1_FFT
Total questions: 20
Worksheet time: 10mins
The Fourier Transform of f(x) is F[f(x)]=
2π1∫−∞∞f(x) dx = F[s]
2π1∫−∞∞f(x)eisx dx = F[s]
2π1∫−∞∞f(x) ds = F[s]
2π1∫−∞∞f(x) cossx dx = F[s]
The inverse Fourier Transform of F[f(x)] is f(x) =
2π1∫−∞∞ F[s] dx = f(x)
2π1∫−∞∞F[s]eisx ds =f(x)
2π1∫−∞∞F[s] e−isxds =f(x)
2π1∫−∞∞F[s] cossx ds = f(x)
The complex form eisx and e−isx is
eisx = cossx + sinsx and e−isx = cossx − sinsx
eisx = cossx +isinsx and e−isx = cossx −isinsx
eisx = cossx and e−isx = sinsx
None of the above
The Real part of eisx is
sinsx
i sinsx
cossx
cosx
The Imaginary part of eisx is
sinsx
i sinsx
cossx
cosx
The Fourier sine Transform of f(x) is Fs[f(x)]=
2π1∫−∞∞f(x) dx = Fs[s]
2π1∫0∞f(x) sinsx dx = Fs[s]
π2∫0∞f(x) sinsx dx = Fs[s]
2π1∫−∞∞f(x) cossx dx = Fs[s]
The inverse Fourier sine Transform of F−1{Fs[f(x)]} = f(x)
2π1∫−∞∞f(x) ds= Fs[s]
2π1∫0∞ Fs[s]sinsx ds=f(x)
π2∫0∞Fs[s]sinsx ds = f(x)
2π1∫−∞∞ Fs[s] cossx dx =f(x)
The Fourier cosine Transform of f(x) is Fc[f(x)]=
2π1∫−∞∞f(x) cossx dx = Fc[s]
2π1∫0∞f(x) cossx dx = Fc[s]
π2∫0∞f(x) cossx dx = Fc[s]
2π1∫−∞∞f(x) cossx dx = Fs[s]
Infinite Fourier Transform pair is also called
complex form
Complex pair
complex transform pair
none of the above
f(x)= x2 in the interval ∣x∣ ≤1 means what and find the value of f(0) ?
f(x)= x2 in the interval x ≤1 and f(0) =1
f(x)= x2 in the interval −1≤x ≤1 and f(0) = 1
f(x)= x2 in the interval 0≤x ≤1 and f(0) = 0
f(x)= x2 in the interval −1≤x ≤1 and f(0) = 0
f(x)=a2− x2 in the interval ∣x∣ ≤a , where a>0 means what and find the value of f(0) ?
f(x)= a2−x2 in the interval x ≤a and f(0) =1
f(x)= a2−x2 in the interval −a≤x ≤a and f(0) = a2
f(x)=a2− x2 in the interval 0≤x ≤1 and f(0) = a2
f(x)= a2−x2 in the interval −a≤x ≤a and f(0) = 0
Given that W=e-i(2π/N) , where N=3. Then F=WN can be computed as F=
0
1
-1
e
Given that W=e-i(2π/N) , where N=3. Then F=W(N/2) can be computed as F=
0
1
-1
e
Which of the following relations are true if x(n) is real?
X(ω)=X(-ω)
X(ω)=-X(-ω)
X*(ω)=X(ω)
X*(ω)=X(-ω)
The time system which operates with a continuous time signal and produces a continuous time output signal is
CTF system
DTF System
Time invariant System
Time variant System
DFT is applied to
Infinite sequences
Finite discrete sequences
Continuous infinite signals
Continuous finite sequences
The circular convolution of two sequences in time domain is equivalent to
Multiplication of DFTs of two sequences
Summation of DFTs of two sequences
Difference of DFTs of two sequences
Square of multiplication of DFTs of two sequences
The basic properties of DFT includes
1)Linearity
2) Periodicity
3) Circular symmetry
4) Summation
1, 2 and 3 are correct
1, 2 and 4 are correct
1 and 3 are correct
All the four are correct
The DFT is preferred for
1) Its ability to determine the frequency component of the signal
2) Removal of noise
3) Filter design
4) Quantization of signal
1, 2 and 3 are correct
1 and 2 are correct
1 and 3 are correct
All the four are correct
DTFT is the representation of
Periodic Discrete time signals
Aperiodic Discrete time signals
Aperiodic continuous signals
Periodic continuous signals
