information theory & coding
Semester : V
Course Code : 18EC54
CIE Marks : 40 SEE Marks : 60
information theory & coding
18EC54
SYLLABUS
Module-1
Information Theory: Introduction, Measure of information, the Information content of the message, Average Information content of symbols in Long Independent sequences, Average Information content of symbols in Long dependent sequences, Markov Statistical Model for Information Sources, Entropy and Information rate of Markoff Sources (Section 4.1, 4.2 of Text 1)
Module-2
Source Coding: Encoding of the Source Output, Shannon’s Encoding Algorithm(Sections 4.3, 4.3.1 of Text 1), Shannon Fano Encoding Algorithm (Section 2.15 of Reference Book 4)
Source coding theorem, Prefix Codes, Kraft McMillan Inequality property – KMI, Huffman codes (Section 2.2 of Text 2)
Module-3
Information Channels: Communication Channels, Discrete Communication channels Channel Matrix, Joint probability Matrix, Binary Symmetric Channel, System Entropies. (Section 4.4, 4.5, 4.51,4.5.2 of Text 1)
Mutual Information, Channel Capacity, Channel Capacity of Binary Symmetric Channel, (Section 2.5, 2.6 of Text 2)
Binary Erasure Channel, Muroga,s Theorem (Section 2.27, 2.28 of Reference Book 4)
Module-4
Error Control Coding: Introduction, Examples of Error control coding, methods of Controlling Errors, Types of Errors, types of Codes, Linear Block Codes: matrix description of Linear Block Codes, Error detection & Correction capabilities of Linear Block Codes, Single error correction Hamming code, Table lookup Decoding using Standard Array.
Binary Cyclic Codes: Algebraic Structure of Cyclic Codes, Encoding using an (n-k) Bit Shift register, Syndrome Calculation, Error Detection and Correction (Sections 9.1, 9.2,9.3,9.3.1,9.3.2,9.3.3 of Text 1)
Module-5
Convolution Codes: Convolution Encoder, Time-domain approach, Transform domain approach, Code Tree, Trellis and State Diagram, The Viterbi Algorithm) (Section 8.5 – Articles 1,2 and 3, 8.6- Article 1 of Text 2)