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WorksheetsEC8553_DTSP::Unit-1-DFT & FFT/Weekly Quiz-2
Total questions: 30
Worksheet time: 30mins
FFT algorithm is designed to perform complex operations.
True
False
How many complex multiplications are need to be performed for each FFT algorithm?
(N/2).log N
N.log2N
(N/2).log2N
None of the mentioned
In Overlap save method of long sequence filtering, what is the length of the input sequence block?
L+M+1
L+M
L+M-1
None of the mentioned
Which of the following is true in case of Overlap add method?
M zeros are appended at last of each data block
M-1 zeros are appended at last of each data block
M zeros are appended at first of each data block
M-1 zeros are appended at first of each data block
In which of the following methods, the input sequence is considered as shown in the below diagram?
Overlap save method
Overlap add method
Overlap add & save method
None of the mentioned
In which of the following methods, the output sequence is considered as shown in the below diagram?
Overlap save method
Overlap add method
Overlap add & save method
None of the mentioned
If we split the N point data sequence into two N/2 point data sequences f1(n) and f2(n) corresponding to the even numbered and odd numbered samples of x(n), then such an FFT algorithm is known as
decimation-in-frequency algorithm.
decimation-in-time algorithm.
Both
None of the mentioned
The total number of complex additions required to compute N point DFT by radix-2 FFT is?
N.log2N
(N/2).log2N
(N/2).log N
None of the mentioned
The following butterfly diagram is used in the computation of __________
Decimation-in-time FFT
Decimation-in-frequency FFT
Both
None of the mentioned
The following butterfly diagram is used in the computation of __________
Decimation-in-time FFT
Decimation-in-frequency FFT
Both
None of the mentioned
For a decimation-in-time FFT algorithm, which of the following is true?
Both input and output are in order
Both input and output are shuffled
Input is shuffled and output is in order
Input is in order and output is shuffled
The Cooley–Tukey algorithm of FFT is a
Divide and conquer algorithm
Divide and rule algorithm
Split and rule algorithm
Split and combine algorithm
FFT may be used to calculate
1) DFT
2) IDFT
3) Direct Z transform
4) In direct Z transform
1, 2 and 3 are correct
1 and 2 are correct
1 and 3 are correct
All the four are correct
DIT algorithm divides the sequence into
Positive and negative values
Even and odd samples
Upper higher and lower spectrum
Small and large samples
The computational procedure for FFT algorithm takes
Log2 N stages
2Log2 N stages
Log2 N2 stages
Log2 N/2 stages
What is the value of x(n)*h(n), 0≤n≤11 for the sequences x(n)={1,2,0,-3,4,2,-1,1,-2,3,2,1,-3} and h(n)={1,1,1} if we perform using overlap save fast convolution technique?
{1,3,3,-1,1,3,5,2,-2,2,3,6}
{1,2,0,-3,4,2,-1,1,-2,3,2,1,-3}
{1,2,0,3,4,2,1,1,2,3,2,1,3}
1,3,3,1,1,3,5,2,2,2,3,6}
Overlap add and Overlap save are the two methods for linear FIR filtering a long sequence on a block-by-block basis using DFT.
True
False
Circular shift of an N point is equivalent to
Circular shift of its periodic extension and its vice versa
Linear shift of its periodic extension and its vice versa
Circular shift of its aperiodic extension and its vice versa
Linear shift of its aperiodic extension and its vice versa
The overlap methods are used to calculate
The discrete convolution between a sampled signal and a finite impulse response (FIR) filter
The discrete convolution between a sampled signal and an infinite impulse response (IIR) filter
The discrete convolution between a very long signal and a finite impulse response (FIR) filter
The discrete convolution between a very long signal and a infinite impulse response (IIR) filte
The first six points of the 8-point DFT of a real valued sequence are 5, 1 −
𝑗3, 0, 3 − 4𝑗, and 3 + 𝑗4. The last two points of the FFT outputs are respectively
0, 1 − 𝑗3
0, 1 + 𝑗3
1 + 𝑗3, 5
1 − 𝑗3, 5
The interface between an analog signal and a digital processor is
D/A converter
A/D converter
Modulator
Demodulator
The cost of the digital processors is cheaper because
Processor allows time sharing among a number of signals
The hardware is cheaper
Require less maintenance
Less power consumption
If the desired number of values of the DFT is less than log2N, a direct computation of the desired values is more efficient than FFT algorithm.
True
False
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
What is the sequence y(n) that results from the use of four point DFTs if the impulse response is h(n)={1,2,3} and the input sequence x(n)={1,2,2,1}?
{9,9,7,11}
{1,4,9,11,8,3}
{7,9,7,11}
{9,7,9,11}
Which of the following is true regarding the number of computations requires to compute an N-point DFT?
N2 complex multiplications and N(N-1) complex additions
N2 complex additions and N(N-1) complex multiplications
N2 complex multiplications and N(N+1) complex additions
N2 complex additions and N(N+1) complex multiplications
If x(n) and X(k) are an N-point DFT pair, then X(k+N)=?
X(-k)
-X(k)
X(k)
None of the mentioned
What is the circular convolution of the sequences x1(n)={2,1,2,1} and x2(n)={1,2,3,4}?
{14,14,16,16}
{16,16,14,14}
{2,3,6,4}
{14,16,14,16}
Frequency selectivity characteristics of DFT refers to
Ability to resolve different frequency components from input signal
Ability to translate into frequency domain
Ability to convert into discrete signal
None of the above
Roll-off factor is
The bandwidth occupied beyond the Nyquist Bandwidth of the filter
The performance of the filter or device
Aliasing effect
None of the above
