EC-702 (B) RGPV B.Tech
Information Theory and Coding (ITC)
Previous year papers and the official syllabus are free to read, no account needed.
Previous Year Papers
2 papers, latest Jun 2025
Syllabus, notes and important questions for EC-702 (B)
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Information Theory 7 topics
- Introduction to uncertainty, entropy and its properties
- Entropy of binary memoryless source and its extension to discrete memory‑less source
- Measure of information
- Information content of message
- Average information content of symbols
- Self information
- Mutual information and its properties
Unit 2 Coding theorem 9 topics
- Source coding theorem
- Prefix coding
- Shannon’s encoding algorithm
- Shannon‑Fano encoding algorithm
- Huffman coding
- Extended Huffman coding
- Arithmetic coding
- Lempel‑Ziv coding
- Run‑length encoding
Unit 3 Information Channels 10 topics
- Communication channels
- Channel models
- Channel matrix
- Joint probability matrix
- Discrete memory‑less channels
- Binary symmetric channel and its channel capacity
- Channel coding theorem and its application to binary erasure channel
- Shannon’s theorem on channel capacity
- Capacity of channel of infinite bandwidth
- Continuous channels
Unit 4 Error Control Coding 6 topics
- Introduction and examples of error control coding
- Methods of controlling errors
- Types of errors
- Types of codes
- Linear block codes: matrix description, error detection and correction capabilities, probability of undetected error for linear block code in BSC, Hamming codes and their applications
- Cyclic codes: basic properties, encoding using an (n‑k) shift register, generator and parity‑check matrix, encoding and decoding circuits, syndrome computation, error detection and correction
Unit 5 Advanced Coding Techniques 3 topics
- Introduction to BCH codes, encoding and decoding, error location and correction
- Convolutional codes: construction, convolution encoder, time‑domain approach, transform‑domain approach, code tree, trellis and state diagram
- Viterbi algorithm: theorem for maximum‑likelihood decoding