State the models for lossless compression and explain any one in. (4 Mark)
What is Data Compression? Compare Lossy Compression with Lossless Compression. (3 Mark)
Chapter 2:- Mathematical Preliminaries for Lossless Compression Models.
Write a short note on Uniquely decodable codes. (4 Mark)
Explain modeling and coding. Explain how this will help to reduce
entropy with suitable example. (7 Mark)
Write a short note on Prefix Code. (3 Mark)
The probability model is given by P(a1) = 0.2, P(a2) = 0.3 and P(a3) =
0.5. Find the real valued tag for the sequence a1a1 a3 a2 a3 a1. (Assume
cumulative probability function: F(0) = 0). (7 Mark)
Determine whether the following codes are uniquely decodable or not. 1. {0, 01, 11, 111} 2. {0, 10, 110, 111} (3 Mark)
Explain different types of models in Data Compression. (4 Mark)
Explain Diagram Coding with suitable example. (4 Mark)
Explain Markov Model with example. (7 Mark)
Chapter 3:- Huffman Coding.
Explain Huffman Coding in detail with example. Define minimum variance Huffman codes. (7 Mark)
Encode “aacdeaab” using Adaptive Huffman code. Derive Output string, Codes and final tree.
Generate GOLOMB code for m=9 and n=8 to 13. (7 Mark)
Write procedure to generate TUNSTALL code. Generate TUNSTALL code
with probability of P(A)=0.6, P(B)=0.3, P(C)=0.1 and n=3 bits. (7 Mark)
Explain Huffman Coding with respect to minimum variance
Huffman codes with separate trees. (7 Mark)
Write a different Application of Huffman Coding. (3 Mark)
Determine the minimum variance Huffman code with the given
probabilities. (4 Mark)
P(a1) = 0.2, P(a2) = 0.4, P(a3) = 0.2, P(a4) = 0.1 and P(a5) = 0.1.
Explain audio compression technique with suitable diagram. (7 Mark)
Explain Rice Codes in brief. (3 Mark)
Design a minimum variance Huffman code for a source that put out letter from
an alphabet A={ a1, a2, a3, a4, a5, a6} with P(a1)=P(a2)=0.2, P(a3)=0.25,
P(a4)=0.05, P(a5)=0.15,P(a6)=0.15.Find the entropy of the source, avg. length
of the code and efficiency. Also comment on the difference between Huffman
code and minimum variance Huffman code. (7 Mark)
Design a minimum variance Huffman code for a source that put out
letter from an alphabet A={a1,a2,a3,a4,a5,a6} with P(a1)=P(a2) =
0.2 , P(a3)=0.25,P(a4)=0.05,P(a5)=0.15,P(a6)=0.15.Find the entropy
of the source, avg. length of the code and efficiency. (7 Mark)
Chapter 4:- Arithmetic Coding.
Define Arithmetic Coding. Encode and Decode “BACBA” with arithmetic coding. (P(A)=0.5,P(B)=0.3,P(C)=0.2). (7 Mark)
Encode and Decode “AABBC” with arithmetic coding. (P(A)=0.6,
P(B)=0.3, P(C)=0.1). (7 Mark)
Write pseudocode for integer arithmetic encoding and decoding
algorithm. (7 Mark)
Compare Arithmetic Coding with Huffman Coding. (4 Mark)
Write the method to generate a tag in Arithmetic Coding. (4 Mark)
Explain Uniqueness and Efficiency of the Arithmetic Code. (3 Mark)
Chapter 5:- Dictionary Techniques.
Given an initial dictionary consisting of the letters a b r y ḇ, encode the following
message using the LZW algorithm: aḇbarḇarrayḇbyḇbarrayarḇbay. (7 Mark)
Encode the following sequence using the LZ77 and LZ78 algorithm: (7 Mark)
ḇarrayarḇbarḇbyḇbarrayarḇba
Assume you have a window size of 30 with a look-ahead buffer of size 15.
Furthermore assume that C(a)=1, C(b)=2, C(ḇ)=3, C(r)=4, and C(y)=5. *
Encode the following sequence using Diagram Coding of Static
Dictionary method (Generate for 3 bit): abracadabra. (7 Mark)
Given an initial dictionary Index 1=w, 2=a, 3=b, encode the
following message using the LZ78 algorithm:
wabba/bwabba/bwabba/bwabba/bwoo/bwoo/bwoo. (7 Mark)
Explain LZ77 with suitable example. (7 Mark)
Encode the following sequence cabracadabrarrarrad using LZ77 Method.
Assume window size of 13 and look ahead buffer of size 6. (7 Mark)
Chapter 6:- Predictive Coding.
Encode the sequence etaḇcetaḇandḇbetaḇceta using Burrows-Wheeler
transform and move to front coding.* (7 Mark)
Write a short note on Old JPEG standard and JPEG-LS. (7 Mark)
Explain CALIC. (3 Mark)
Explain prediction with partial match in short. (3 Mark)
Explain Facsimile Encoding and Exclusion principle in detail. (4 Mark)
Chapter 7:- Mathematical Preliminaries for Lossy Coding.
Explain nonuniform quantization. (3 Mark)
Explain pdf optimized quantization. (3 Mark)
Explain structured vector quantizers. (3 Mark)
Explain pyramid vector quantization. (3 Mark)
Explain adaptive quantization with any one approach. (4 Mark)
Chapter 8:- Vector Quantization.
Explain Scalar Quantization in detail. (7 Mark)
Explain Vector Quantization in detail. (7 Mark)
Explain Linde-Buzo-Gray algorithm in detail. (4 Mark)
Chapter 9:- Boolean retrieval.
Explain and compare Incident matrix and Inverted index with example. (7 Mark)
Explain skip pointers and Phrase queries with example. (7 Mark)
Explain Tokenization. (3 Mark)
Explain Information Retrieval in detail. (4 Mark)
Write a short note on Phrase queries with example. (4 Mark)
Explain stemming and lemmatization with suitable example. (7 Mark)
Chapter 10:- XML retrieval.
Explain challenges in XML information retrieval. (7 Mark)
Explain Vector Space Model in XML. (4 Mark)
Write a short note on : I) Positional Index II) data-centric XML retrieval. (7 Mark)
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