Deemed University 2010 M.Tech Electronics and Communication Engineering University: Lingayas University Term: III Title of the : ADVANCED DIGITAL SIGNAL PROCESSING - Question Paper

Roll No. ..

 

Lingayas University, Faridabad

M.Tech (Part-Time) Electronics & Comm. Engg.

Term-III Examination May, 2010

ADVANCED DIGITAL SIGNAL PROCESSING (EC -506)

[Time: 3 Hours] [Max. Marks: 100]

 

Before answering the question, candidate should ensure that they have been supplied the correct and complete question paper. No complaint in this regard, will be entertained after examination.

 

Note: Question No. 1 Section A is compulsory. Attempt any two questions from Section B and any two questions from Section C. In all attempt five questions.

Section A

Q-1. (i) Why are FIR filters widely used for adaptive filters? (5x4=20)

(ii) Give the basic principle of Levinson recursion.

(iii) What is meant by image smoothing and image sharpening?

(iv) Compute the energy of a discrete signal x(n) in time and frequency domains?

(v) Write Yule-walker equations for ARMA model Parameter.

Section B

Q-2. What do you understand by an adaptive filter? Discuss the minimum MSE criterion to develop an adaptive FIR filter. (20)

Q-3. Derive the principle of orthogonality for the Winear FIR filter and Show that Winear filter can Work as filter and predictor. (20)

Q-4. Explain the continuous wavelet transform and the application of wavelets in signal compression. (20)

 

 

Section C

Q-5. Present the model based approach to power spectral estimation. Define AR, MA, and ARMA models Illustrate the ARMA model for spectrum estimation (20)

Q-6. Consider a signal x(n) = s(n) + w(n) where s(n) is an AR(1) process that satisfies the difference

equation s(n) = 0.6 s(n-1)+ v(n) where v(n) is a white noise sequence with variance =0.64 and w(n) is a white noise sequence with variance = 1.

Design a wiener filter of length M=2 to estimate s(n). (20)

Q-7. Design a decimator that downsamples an input signal x(n) by an factor D=2.use the Remez algorithm to determine the coefficient of FIR filter that has a 0.1 dB ripple in the passband and is down by at least 30 dB in the stopband. (20)

Q-8. Explain the adaptive channel equalization in detail. (20)

Roll No. ..

 

Lingayas University, Faridabad

M.Tech (Part-Time) Electronics & Comm. Engg.

Term-III Examination May, 2010

ADVANCED DIGITAL SIGNAL PROCESSING (EC -506)

[Time: 3 Hours] [Max. Marks: 100]

 

Before answering the question, candidate should ensure that they have been supplied the correct and complete question paper. No complaint in this regard, will be entertained after examination.

 

Note: Question No. 1 Section A is compulsory. Attempt any two questions from Section B and any two questions from Section C. In all attempt five questions.

Section A

Q-1. (i) Why are FIR filters widely used for adaptive filters? (5x4=20)

(ii) Give the basic principle of Levinson recursion.

(iii) What is meant by image smoothing and image sharpening?

(iv) Compute the energy of a discrete signal x(n) in time and frequency domains?

(v) Write Yule-walker equations for ARMA model Parameter.

Section B

Q-2. What do you understand by an adaptive filter? Discuss the minimum MSE criterion to develop an adaptive FIR filter. (20)

Q-3. Derive the principle of orthogonality for the Winear FIR filter and Show that Winear filter can Work as filter and predictor. (20)

Q-4. Explain the continuous wavelet transform and the application of wavelets in signal compression. (20)

 

 

Section C

Q-5. Present the model based approach to power spectral estimation. Define AR, MA, and ARMA models Illustrate the ARMA model for spectrum estimation (20)

Q-6. Consider a signal x(n) = s(n) + w(n) where s(n) is an AR(1) process that satisfies the difference

equation s(n) = 0.6 s(n-1)+ v(n) where v(n) is a white noise sequence with variance =0.64 and w(n) is a white noise sequence with variance = 1.

Design a wiener filter of length M=2 to estimate s(n). (20)

Q-7. Design a decimator that downsamples an input signal x(n) by an factor D=2.use the Remez algorithm to determine the coefficient of FIR filter that has a 0.1 dB ripple in the passband and is down by at least 30 dB in the stopband. (20)

Q-8. Explain the adaptive channel equalization in detail. (20)