Information Theory and Coding CS-722

Information Theory and Coding (CS-722)

Course Type: Programme Elective-II
Batch: 4th Year CSE, Dual Degree
Course Credits: 04

To learn concepts in information theory, and the performance characteristics of an ideal communications system.
To know about the fundamentals in Information coding and its applications.

There are no official pre-requisites for this course.

Vivekananda Lecture Hall (B3)

Monday: 12:00 PM - 01:00 PM
Tuesday: 12:00 PM - 01:00 PM
Wednesday: 12:00 PM - 01:00 PM
Thursday: 12:00 PM - 01:00 PM

Introduction to information Theory, Information and entropy, properties of entropy of a binary memoryless source.
Measure of Information, Source Coding, Shannon Fano coding, Huffman coding, Lempel Ziv coding, channel coding, Channel capacity, noisy channel.
Coding theorem for DMC. Linear block codes, generator matrices, parity check matrices.
Encoder syndrome and error detection minimum distance, error correction and error detection capabilities, cyclic codes, coding and decoding.
Coding convolutional codes, encoder, generator matrix, transform domain representation state diagram, distance properties.
Maximum likelihood decoding, Viterbi decoding, sequential decoding, interleaved convolutional codes.

Upon successful completion of the course, the students will be able to:

CO1: Understand how the quantity of information could be measured.
CO2: Understand the concept and properties of entropy and mutual information as applied to information.
CO3: Construct compact and non-compact codes for a given data ensemble.

Information Theory Coding and Cryptography by R. Bose, Tata McGraw Hill.
The Theory of Error Correcting Codes by F. J. MacWilliams and N. J. A. Sloane, Elsevier.
Coding and Information Theory by S. Roman, Springer.
The Theory of Information and Coding by R. J. McEliece, Cambridge University Press.
Elements of Information Theory by T. M. Cover and J. A. Thomas, Wiley.