**Digital Signal Processing LAB VIVA Questions :-**

**1. Define discrete time and digital signal.**

Discrete time signal is continuous in amplitude and discrete in time, where Digital signal is discrete in time and amplitude.

**2. Explain briefly, the various methods of representing discrete time signal**

Graphical, Tabular, Sequence, Functional representation

**3. Define sampling and aliasing.**

Converting a continuous time signal into discrete time signal is called as Sampling, Aliasing is an effect that causes different signals to become indistinguishable.

**4. What is Nyquist rate?**

Its the sampling frequency which is equal to twice of Continuous time signal which has to be sampled.

**5. State sampling theorem.**

It states that , To reconstruct the continuous time signal from its Discrete time signal, The sampling frequency should be more than twice of continuous time signal frequency.

**6. Express the discrete time signal x(n) as a summation of impulses.****7. How will you classify the discrete time signals?**

Causal and Non causal, Periodic and non periodic, even and odd, energy and power signals

**8.. When a discrete time signal is called periodic?**

If some set of samples repeats after a regular interval of time then its called as periodic.

**9. What is discrete time system?**

If a system’s excitation and responses are both discrete time signals then its called as discrete time 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.**

**12. classifying discrete time systems.**

Causal, Non causal, time variant, time invariant, Linear, non linear, stable and unstable system.

**13. Define time invariant system.**

If a system’s operation is independent of time then its time invariant, i.e delayed system response is equal to system’s response for delayed input.

**14. What is linear and nonlinear systems?**

If a system satisfies homogeneity principle and superposition principle then it is Linear. if not Non linear.

**15. What is the importance of causality?**

causality states that system’s response should depend on present and past inputs only not on the future inputs. so causal systems are realizable.

**16. What is BIBO stability? What is the condition to be satisfied for stability?**

If a system’s response is Bounded for Bounded excitation then its BIBO stable.

For stable system the impulse response should be absolutely sum able .

**17. What are FIR and IIR systems?**

**FIR:**system’s impulse response contains finite no. of samples**IIR:**system’s impulse response contains infinite no. of samples

**18. What are recursive and non recursive systems? give examples?**

A Recursive system is one in which the output depend on it,s one or more past outputs while a non recursive is one in which output is independent of output.

**Ex:** any system with feedback is Recursive , without feedback is non recursive.

**19. Write the properties of linear convolution.**

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. Define circular convolution.**

Circular convolution is same as linear convolution but circular is for periodic signals.

**21. What is the importance of linear and circular convolution in signals and systems?**

Convolution is used to calculate a LTI system’s response for given excitation.

**22. How will you perform linear convolution via circular convolution?**

circular convolution with the length of linear convolution length (l+m-1) results linear convolution.

**23. What is sectioned convolution? Why is it performed?**

If any one of the given two sequences length is very high then we have to go for sectioned convolution.

**24. What are the two methods of sectioned convolution?**

1) Over lap-Add method. 2) Over lap save method.

**25. Define cross correlation and auto-correlation?**

Auto correlation is a measure of similarity between signals and its delayed version as a function of time delay.

cross correlation is a measure of similarity between two signals as a function of time delay between them.

**26. What are the properties of correlation?**

1) R12(T)≠R21(T)

2) R12(T)=R21*(-T)

3) if R12(T)=0, both signals are orthogonal to each other

4) Fourier transform of auto correlation gives energy spectral density.

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