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Monday, 6 July 2020

Digital Signal Processing (DSP) Viva Questions and Answers


Viva Questions and Answers on Digital Signal Processing

1. Differentiate between a discrete time signal and a digital signal.

A discrete time signal can be defined as a signal, which is continuous in amplitude and discrete in time. In other words, a discrete time signal gives signal values only at particular (discrete) interval of time periods.
A digital signal represents signal as a sequence of discrete values. That is, a digital signal takes values from a given set of finite number of values. Digital signals are most commonly used in communication systems.
2. How we can represent a discrete time signal?

A discrete time signal can be represents in Graphical form, Tabular form, Sequence and as Functional representation.

3. Explain the process of sampling and define aliasing effect.

The process of converting a continuous time signal into a time signal is known as sampling. In order to convert, a continuous time signal is passed through a switch. The frequency of the switch is the sampling rate (Fs).
The Aliasing is an effect that occurs at the time of reconstruction of the sampled signal. This effect occurs, when the Sampling frequency (Fs) is less than two times the maximum frequency present in the signal component. Fs< = 2 Fm. The aliasing effect causes different signals to become indistinguishable.
4. What is the need of Nyquist rate in sampling process?

The sampling process is completely depends on the nyquist rate. The nquist rate is the sampling frequency, which is equal to twice of maximum frequency of the continuous time signal which has to be sampled. i.e, Fs= 2 Fm. If nyquist rate is maintained, we get perfect sampling. The sampling rate which is greater than the nyquist rate is called over sampling. The rate less than nyquist rate gives under sampling. A signal cannot be reconstructed from its samples, if it is under sampled.

5. State and discuss sampling theorem.

Sampling theorem states that, in order to reconstruct the continuous time signal from its samples (its discrete signals), the sampling frequency should be more than twice of  the maximum frequency present in the continuous time signal.

6. How you express a discrete time signal x(n) in terms of summation of impulses.

A discrete time signal can be represented as summation of impulse by,
7. Give the classification of discrete time signals?

A discrete time signal can be classified as: Causal and Non causal, Periodic and non periodic, even and odd, energy and power signals.

8. When you called a discrete time signal as a periodic signal?

A discrete time signal can be called as a periodic signal, if some set of samples of the signal repeats after a regular interval of time.

9. Describe about a discrete time system?

Basically a system is a device which takes a signal as input and gives another signal as output. A system is said to be a discrete time system, if the system's excitation and responses are both discrete time signals. In other words, a discrete time system takes a discrete time input signal and gives a discrete signal as output. The ratio of output signal to input signal is the transfer function of the system.

10. What is impulse response? Explain its significance.

The response of a system when the excitation is Impulse signal is called as impulse response. it also called as Natural response, free forced response.

11. Write the expression for discrete convolution.

The process of discrete convolution can be represented as:

12. Explain the classification of discrete time systems.

The discrete time systems are classified as causal, non causal, time variant, time invariant, linear, non linear, stable and unstable systems.

13. What you understand about time invariant system.

For a time invariant system, the system's operation is independent of time. In other words, we can say that if the delayed system response is equal to system's response for delayed input, then the system is known as time invariant system.

14. Distinguish between linear and nonlinear systems?

A system is said to be a linear system, if the system satisfies homogeneity principle and superposition principle. If a system doesn’t satisfy homogeneity and superposition principles, then the system is a not non linear system.

15. What you know about causality?

A system is said to be a causal, if the system's response should depend on present and past inputs only and not on the future inputs. That is causal systems are physically realizable systems. Non causal systems response depends on the future input values. Hence non causal systems are physically non realizable systems.

16. What you know about BIBO stability? Discuss the condition to be satisfied for stability?

A system is said to be BIBO stable, if the system's response is bounded (measurable) for bounded excitation. In other words, if the system’s output is measurable for the measurable input, the system is said to be BIBO stable.  For a system to be stable, the impulse response of the system should be absolutely summable.

17. Compare between FIR and IIR systems?

If the system's impulse response contains finite number of samples, then the system is a FIR system.
If the system's impulse response contains infinite number of samples, then the system is said to be an IIR system.

18. Discuss in detail about recursive and non recursive systems?

If the output depend on it’s one or more past outputs, then the system is said to be a recursive system. If the output is independent of output, then the system is said to be non recursive.
All systems with feedback are Recursive. Systems without feedback are non recursive. 

19. Discuss about the properties of linear convolution.

The properties of linear convolution are:

1) x(n)*y(n)= y(n)*x(n)
2) [x(n)+y(n)]*z(n)=x(n)*z(n)+y(n)*z(n)
3) [x(n)*y(n)]*z(n) =x(n)*[y(n)*z(n)]

20. What you know about circular convolution.

Actually linear convolution and circular convolution are same. Circular is for periodic signals.

21. Discuss the need of linear and circular convolution?

Actually convolution is mainly used for calculating the response of a LTI system for a given excitation.

22. How the process of linear convolution via circular convolution is performed?

Linear convolution is obtained when circular convolution with the length of linear convolution length (l+m-1) is performed.

23. Describe about sectioned convolution?

Sectioned convolution is performed, if any one of the given two sequences length is very high.  

24. List the two types of sectioned convolution?

The two different types of sectioned convolution are:
1) Over lap-Add method. 2) Over lap save method.

25. Differentiate the process of cross correlation and auto-correlation?

The measure of similarity between signals and its delayed version as a function of time delay is called as auto-correlation. Auto correlation is also known as serial correlation.

The measure of similarity between two signals as a function of time delay between them is known as cross-correlation. Cross correlation is also known as sliding dot product.

26. Discuss the properties of correlation?

The important properties of correlation are:

1) R12(T) ≠ R21(T)
2) R12(T) = R21*(-T)
3) if R12(T) = 0, if the two signals are orthogonal to each other
4) The energy spectral density can be obtained from the Fourier transform of the auto correlation.

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