MCSIS105-4 Information Theory & Coding M.Tech Model Question Paper : mgu.ac.in

Name of the College : Mahatma Gandhi University
Department : Computer Science and Engineering
Subject Code/Name : MCSIS 105-4/Information Theory And Coding
Sem : I
Website : mgu.ac.in
Document Type : Model Question Paper

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MGU Information Theory & Coding Question Paper

M.TECH. Degree Examination,
Branch: Computer Science Engineering
Specialization: Information Systems

Related : MGU MCSIS105-1 High Performance System Architecture M.Tech Model Question Paper : www.pdfquestion.in/5021.html

Model Question Paper – I
First Semester
MCSIS 105-4 : Information Theory And Coding
(Regular – 2013 Admissions)
Time: Three Hours
Maximum: 100 marks

December 2013

Answer all questions. :
Any data, if required may be suitably assumed and clearly indicated.
1. (a) Define Information and entropy. Explain joint and conditional entropies. (8 marks)
(b) State and explain Shannon’s channel capacity theorem. (7 marks)

(c) A discrete transmitter transmits one of the 6 symbols, once in every 5 milliseconds with probabilities 0.5, 0.25, 0.125, 0.0625, 0.03125, 0.03125. Find entropy and information rate. (10 marks) OR

2. (a) Define channel coding theorem. (7 marks)
(b) Define discrete memory-less channels. Discuss in detail about its properties. (8 marks)

(c) A Telephone channel has a bandwidth of 8 KHz and SNR of 32. Calculate the channel capacity. If channel capacity is to be 128kbps, what is the signal to noise ratio? (10 marks)

3. (a) Explain Syndrome decoding with example. (12 marks)
(b) Consider convolution code(3, 1, 2) with g(1) = (110), g(2)=(101), g(3)=(111). Find generator matrix. Find code for the word sequence for the information sequence (11101) using domain time approach. (13 marks)
OR

4. (a) Explain the error detection and correction capability of a Standard array decoding (10 marks)
(b) Explain how minimum distance codes are used for error detection with and example. (10 marks)
(c) What is Trellis diagram. Give an example. (5 marks)

5. (a) Explain Viterbi algorithm with an example. (10 marks)
(b) Discuss the Hamming code for 1 bit error correction with example. (10 marks)
(c) Explain BCH code. (5 marks)
OR

6. (a) Explain Stack (ZJ) decoding algorithm with example. (15 marks)
(b) What is Linear block code? Discuss systematic and non-systematic codes (10 marks)

7. (a) A discrete system sends 7 symbols with probabilities 0.25, 0.25, 0.125, 0.125, 0.125, 0.0625, 0.0625. Calculate Shannon-Fanno Elias code. (15 marks)
(b) State explain Source coding theorem with appropriate examples. (10 marks)
OR

8. (a) State and prove Krafts inequality. (12 marks)
(b) Explain Arithmetic coding with examples (13 marks)

December 2014

Information Theory & Coding
(Regular – 2013 Admissions)
Time: Three Hours
Maximum: 100 marks
Answer all questions. :
Any data, if required may be suitably assumed and clearly indicated.
1. (a) Define Information and entropy. Explain joint and conditional entropies. (7 marks)
(b) State and explain Shannon’s channel capacity theorem. (6 marks)

(c) Consider that two sources emit messages xl, x2, x3 and y1, y2, y3 with the joint probabilities
p (X, Y) as shown in the matrix form:
(i) Calculate the entropies of X and Y. (4 marks)
(ii) Calculate the joint and conditional entropies, H (X,Y), H (X/Y), H(Y/X) between X and Y. (6 marks)
(iii) Calculate the average mutual information I(X;Y). (2 marks)
OR

2. (a) Explain Zero-error codes. (7 marks)
(b) Discuss about BSC and BEC. (8 marks)
(c) A Telephone channel has a bandwidth of 8 KHz and SNR of 32. Calculate the channel capacity. If channel capacity is to be 128kbps, what is the signal to noise ratio? (10 marks)

3. (a) Explain Syndrome decoding with example. (12 marks)
(b) Consider convolution code(2, 1, 3) with g(1) = (100), g(2)=(110), g(3)=(111). Find generator matrix. Find code for the word sequence for the information sequence (11001) using domain time approach. (13 marks)
OR

4. (a) Explain the working of CRC with an example. (15 marks)
(b) What are the differences between Trellis diagram and state diagram? (10 marks)
5. (a) Explain Viterbi algorithm with an example. (10 marks)

(b) Explain the working of (2,1,3). Convolution encoder using transform domain approach. (10 marks)
(c) Explain LDP code. (5 marks)
OR

6. (a) Explain Stack (ZJ) decoding algorithm with example. (15 marks)
(b) What is the principle behind choosing the Hamming bit positions for error correction? (10 marks)

7. (a) Explain the basic principles behind Turbo coding (9 marks)
(b) State Kraft’s inequality. (6 marks)
(c) Explain the concept behind Huffman codes. State some of the application domains of Huffman codes. (10 marks)
OR

8. (a) Given 8 symbols A,B,C,D,E,F,G and H with probabilities 1/20, 1/20, 1/20, 1/10, 3/20, 3/20, 1/5 and 1/4 respectively, construct the Huffman tree. (15 marks)
(b) Evaluate the differences between Huffman codes and Adaptive Huffman codes. (4 marks)
(c) Explain the basic principle behind ZIP coding. (6 marks)