# Advanced Digital Signal Processing 1st AM11 AP9211

M.E. DEGREE EXAMINATION, APRIL/MAY 2011
First semester
Applied Electronics
(Common to M.E Communication Systems and M.E. Computer and Communication)
(Regulation 2009)

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PART A—(10 × 2 = 20 marks)

1. State Parseval’s theorem.
2. State two properties of autocorrelation.
3. What are the demerits of the periodogram?
4. Define bias and consistency.
5. Name any one application of the AR model.
6. What is a whitening filter?
8. What are the principles of LMS algorithm?
9. Name two applications of multirate sampling.
10. Define discrete wavelet transform.

PART B—(5 × 16 = 80 marks)

11. (a) State and prove Wiener Khinchine theorem.
Or
(b) Obtain the filter to generate a random process with a power spectrum.
(Px(e pow (iw))=(5+4 cos 2w)/(10+6 cos w) from white noise.

12. (a) (i) Explain how power spectrum can be estimated from the AR model. (8)
(ii) Discuss the Welch method of Periodogram averaging. (8)
Or
(b) Discuss the Blackman-Tukey method.

13. (a) Derive Wiener Hopf equations.
Or
(b) Explain the Prony’s method of solving the normal equations.

14. (a) Discuss adaptive noise cancellation using LMS algorithm.
Or
(b) Explain normalized LMS algorithm.

15. (a) Discuss sampling rate conversion by a rational factor.
Or
(b) Discuss how speech compression can be achieved using sub-band coding.