Digital Signal Processing interview Questions , Viva Questions , Bits

Subject: Digital Signal Processing

                                                    I – Introduction

1). What is random signal?

Ans: A random signal is a signal characterized by uncertainty before its actual occurrence.

2). Define symmetric and anti symmetric signals.

Ans: A real valued signal x(n) is called symmetric if x(-n)=x(n). On the other hand, a signal x(n) is called anti symmetric if x(-n)=-x(n).

3). Represent the following finite duration sequence x(n)={2,4 ,-1,-2} as a sum of weighted impulse sequences.

Ans: 2

4). What is causal system? and give an example.

Ans: A system is said to be causal if the output of the system at anytime n depends only on present and past input, but does not depend on future inputs.

Ex: y(n)= x(n)+x(n-1)

5). Define static and dynamic system.

Ans:

 Static: A static or memory less discrete time system is a system whose output at any instant depends on the input values at that instant but neither on the past nor on the future values of the input.

Ex: y(n)=ax(n)

Dynamic:A dynamic or a system with memory is one in which the past inputs or outputs are stored to calculate the present output.

Ex: y(n)=x(n)+3x(n-1)

6). What is the causality condition for an LTI system?

Ans: The necessary and sufficient condition for causality of an LTI system is, its unit sample response h(n)=0 for negative values of n i.e.  h(n)=0  for  n<0

7). What is the necessary and sufficient condition on the impulse response for stability?

Ans: The necessary and sufficient condition guaranteeing the stability of a linear time invariant system is that its impulse response is absolutely summable     i.e.,    

8). What is time-invariant system?

Ans: If the input-output relation of a system does not vary with time, the system is said to be time-invariant or shift-invariant.

If the output signal of a system shifts k units of time upon delaying the input signal by k units, the system under consideration is a time-invariant system.

Ex: y(n)=x(n)+x(n-1)

9). What are different types of operations performed on discrete-time signals?

Ans: Delaying of signal, advance of signal, folding or reflection of a signal, time scaling, amplitude scaling, addition of signals and multiplication of signals.

10). In digital signal processing system, what is the purpose of anti-aliasing filter?

Ans: This is a LPF used to remove the high frequency noise and to band limit the signal. In addition to the LPF, it may also be advantageous to include a 50Hz notch filter that can remove the power-frequency component, which is a large part of external noise.

11). What is the value of e²ⁿ ?

Ans:1

12). What is the formula for power signal?

Ans:

13). Natural response is also known as   Zero input response .

14). If the roots of the characteristic equation are distinct, then the general solution is

        y _h(n)=

15). If the input signal x(n) is impulse, then the particular solution is   y _p(n)= 0.

16).  If the input signal x(n)= Acoswn or x(n)= Asinwn, then the particular solution is

      y _p(n)=            

17). What are the advantages of digital signal processing?

Ans: Greater accuracy, ease of data storage, flexibility in configuration and time sharing

18). In digital signal processing system, what is the purpose of reconstruction filter?                     

Ans: The purpose of reconstruction filter is to eliminate the high frequency components.

19). What are the applications of DSP?

Ans: Telecommunication, consumer electronics, image processing, military and etc.

20). What is the formula for fundamental period in periodic signals?

Ans:                                                                     

                                   II – DFT and DFS

1). What is the time shifting property of discrete time fourier transform?

Ans: If  F[x(n)] =X() then F[x(n-k)] =

2). If X() is the fourier transform of x(n), what is the fourier transform of nx(n)?

Ans:  F[nx(n)] = j 

3). Find the transfer function of the system given by y(n) - y(n-1) = x(n)+ x(n-1).

Ans: H() =

4). What is the difference between DFS and DFT?

Ans: DFS exists only for periodic signals, where as DFT exists for both periodic and aperiodic

5). What is the relation ship between DFT and Z-T?

Ans:

6). Multiplication of two sequences in time domain is Convolution in frequency domain.

7). What is parseval’s theorem?

Ans:

8). What are the methods to evaluate the circular convolution of two sequences?

Ans: Concentric circle method and matrix multiplication method.

9). What is the advantage of  linear convolution over circular convolution?

Ans: In linear convolution there is no aliasing effect, where as in case of circular convolution there is an aliasing effect.

10). What is the length of output sequence in circular convolution?

Ans: Output sequence length in circular convolution is MAX(N1,N2), where N1 is first sequence length and N2 is second sequence length.

11). What is the disadvantage of overlap-save method?

Ans: In each output block M-1 points are corrupted due to aliasing, as circular convolution is employed.

12). What is the advantage of overlap-add method?

Ans: In this no corruption due to aliasing, as linear convolution is performed using circular convolution.

13). Let X(k) be a 14-point DFT of a length 14 real sequence x(n). The first 8 samples of X(k) are given. Then what is the formula to obtain remaining 6 samples  of X(k).?

Ans: X(k) =  

14). If x(n)=  then DFT[x(n)]=   1

15). If x(n)=  then DFT[x(n)] =        

16). What is the Complex conjugate property of DFT?

Ans: If DFT[x(n)] =X(k) then DFT[(n)] =

17). What is the difference between DFT and DTFT?

Ans:

 DFT: Obtained by performing sampling operation in both the time and frequency spectrum and it has discrete frequency spectrum.

DTFT: Sampling is performed only in time domain and continuous function of w

18). How will you obtain linear convolution from circular convolution?

Ans: Linear convolution is obtained by using circular convolution with zero padding  .

19). What are the two methods used for the sectioned convolution or filtering long duration techniques?

Ans: Overlap-save and overlap-add method.

20). What is the use of filtering long duration techniques?

Ans: If the data sequence x(n) is of long duration, it is very difficult to obtain the output sequence y(n) due to limited memory of a digital computer. Therefore, the data sequence is divided into smaller sections. These sections are processed separately one at a time and combined later to get output.