Download AKTU B-Tech 7th Sem 2015-2016 ECS 077 Data Compression Question Paper

Download AKTU (Dr. A.P.J. Abdul Kalam Technical University (AKTU), formerly Uttar Pradesh Technical University (UPTU) B-Tech 7th Semester (Seventh Semester) 2015-2016 ECS 077 Data Compression Question Paper

Printed Pages : 3 483 ECS?077
(Following Paper ID and Roll No. to be filled in your
Answer Book)
Roll No.
B.Tech.
(SEM. VII) THEORY EXAMINATION, 2015-16
DATA COMPRESSION
[Time : 3 hours] [Total Marks : 100]
Note': Attempt questions 'from all Sections as per directions.
Section-A
1. Attempt all parts of this section. Answer in brief.
(a)
(b)
2900
- (10x2=20)
What is data compression?
Discuss dynafnio'Markov compression with
suitable example.
Differentiate between lossy and lossless
compression.
Explain the predictive coding techniques in data
compression.
Differentiate between LZ77 and LZ78 data
compression techniques.
(1) 'P.T.O.

Attempt any five questions.
2.
2900
( 0 Write advantages of vector quantizatioh over scalar
quantization.
(g) How the Linde-Buzo-Gray algorithm works?
(h) Compare and contrast JPEG and MPEG.
(i) What bene?ts are offered by compression schemes ,
in designing systems?
(j) What are the advantages of using specialized
multimedia'servers?
Section-B
?
(5x10=50)
Why we need date compression? Explain compression
and reconstruction with the help of block diagram.
. ? O
Differentiate between static length and variable length
coding schemes. Explain with the help of examples.
Based upon the requirements of reconstruction how data
comprission techniques are broadly classi?ed. Explain
these classi?cations in brief.
(2) ECS-077
5. What are the measures of performance of data
compression algorithms?
6. What is average information? What are the properties
used i? measurement of average information.
7. Discuss generic compression scheme with?the hepl of
block diagram. What are the distortion criteria for Lossy
coding?
8. Explain uniform and non-uniform quantization with
further classi?cations.
9. Explain the procedure for the adaptive Huffman codding
and encoding algorithm ?owchart.
Section-C
Attempt any two questions. i (2 x 1 5=30)
10. What do you understand by Markov model? Discuss the
role markov models in text compression.
1 1. Explain minimum variance Huffman code and encoding
procedure with suitable example.
12. What is quantization? Explain additive noise of a
quantizer. Differentiate between scalar quantization and
vector quantization. What are the advantages of vector
quantization over scalar quantization?
O _x_
2900 (3) ECS-077