Data Compression (KCS-064) - AKTU Question Paper 2022-23
B.Tech · Semester 6 · Free PDF Download
This is the official AKTU Data Compression Previous Year Question Paper for B.Tech Semester 6, academic session 2022-23. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.
Course:B.Tech
Semester:Semester 6
Session:2022-23
University:AKTU / UPTU
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Questions Asked in 2022-23
Data Compression (KCS-064) — extracted question text
Section AAttempt all questions in brief. 2 x 10 = 20
- aWhat are the different measures of performance of data compression algorithm?
- bGiven an Alphabet A = {a1, a2, a3, a4}, find the first-order entropy in the following cases
- cWhat are the applications of Huffman Coding?
- dCalculate Golomb Code for n=9 and n=13 with parameter m=5
- eList out the applications of dictionary based data compression techniques
- fCompare Binary code with Huffman code
- gWhat are the various distortion criteria?
- hExplain mismatch effect. (i) Define Code Vectors. (j) What is the concept of pruning?
Section BAttempt any three of the following: 10x3=30
- aHow do uniquely decodable codes differ from prefix codes? Explain with example. Describe the procedure for coding a uniquely decoda ble code. Are the following codes {0, 10, 110, 111} {1, 10, 110, 111} uniquely decodable?
- bExplain the difference between Minimum variance Huf fman code and Huffman code with example. From an alphabet A = {a1, a2, a3, a4, a5} with probabilities P(a1) = 0.15, P(a2) = 0.04, P(a3) = 0.26, P(a4) = 0.05 and P(a5) = 0.50. (i) Calculate the entropy of this source. (ii) Find the Huffman Code for this source. (iii) Find the average length of the code in (ii) and its redundancy
- cExplain the basic algorithm behind prediction with p artial match (ppm) .What is Facsimile Encoding? Explain Run-Length Coding technique used earlier for Facsimile
- dWhat do you understand by Adaptive quantization? Ex plain the various approaches to Adapting the Quantizer Parameters
- eWhat do understand by Vector Quantization? Discuss the advantages of vector quantization over scalar
Section CAttempt any one part of the following: 10x1=10
- aDefine two -state Markov model for binary images. Also define i gnorance model and how it is related with probability models?
- bDiscuss the importance of modeling and coding in the compression process with example . How does information theory relate to lossless comp ression? Can you explain some key concepts in information theory and their relevance to compression?
- aGiven an alphabet {a 1, a 2, … , a 26 } of size 26. The letter a k is encoded as per the following rules: k is encoded as 5 bit binary representation of k – 1, if 1 ≤k ≤20 (ii) a k is encoded as 4 bit binary representation of k-11 for all k >20. Decode the following string using Adaptive Huffman procedure. Show updated Huffman tree for each step
- bHow Rice code can be viewed? Explain the implementation of the Rice code in the recommendation for lossless compression from the Consultative Committee on Space Data Standard
- aA sequence is encoded using LZW algorithm and the initial dictionary shown in table Index Entry The output of the LZW encoder is the following sequence: Decode this sequence. Discuss relative advantages of LZ77, LZ78 and LZW Compression schemes
- bExplain Burrows-Wheeler transform (BWT) in detail. Given the sequence: this¢is¢the Encode using the BWT and move-to-front coding
- aWhat do you understand by Uniform Quantizer? How uniform quantization of a uniformly distributed sources and uniform quantization of non-uniform sources is done?
- bConsider the following lossy compression scheme for binary sequences. We divide the binary sequence into blocks of size M. For each blo ck we count the number of 0s.If this number is greater than equal to M/2, we send as 0; otherwise, we send a 1. (i)If the sequence is random with P(0) = 0.8, compu te the rate and distortion for M = 1, 2, 4, 8, 16.Compare your results with the rate distortion function for binary sources. (ii)Repeat assuming that the output of the encoder is encoded at a rate equal to the entropy of the output
- aExplain the various functions involved in the Linde -Buzo-Gray(LBG) Algorithm. Also explain the initializing of LBG algorithm
- bWrite a short note on : (i) Tree structured Vector Quantizers. (ii) Lattice Vector Quantizers
Question text is extracted from the official AKTU question paper PDF above. Check the original PDF for equations, diagrams and complete wording. Extracted: 2026-08-23.
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