Information Theory and Coding

Lecture 1 - Introduction to Information Theory and Coding

Lecture 2 - Definition of Information Measure and Entropy

Lecture 3 - Extention of An Information Source and Markov Source

Lecture 4 - Adjoint of An Information Source, Joint and Conditional Information Measure

Lecture 5 - Properties of Joint and Conditional Information Measures and A Morkov Source

Lecture 6 - Asymptotic Properties of Entropy and Problem Solving in Entropy

Lecture 7 - Block Code and its Properties

Lecture 8 - Instantaneous Code and Its Properties

Lecture 9 - Kraft-Mcmillan Equality and Compact Codes

Lecture 10 - Shannon's First Theorem

Lecture 11 - Coding Strategies and Introduction to Huffman Coding

Lecture 12 - Huffman Coding and Proof of Its Optamality

Lecture 13 - Competitive Optamality of The Shannon Code

Lecture 14 - Non-Binary Huffman Code and Other Codes

Lecture 15 - Adaptive Huffman Coding - Part-I

Lecture 16 - Adaptive Huffman Coding - Part-II

Lecture 17 - Shannon-Fano-Elias Coding and Introduction to Arithmetic Coding

Lecture 18 - Arithmetic Coding - Part-I

Lecture 19 - Arithmetic Coding - Part-II

Lecture 20 - Introdution to Information Channels

Lecture 21 - Equivocation and Mutual Information

Lecture 22 - Properties of Different Information Channels

Lecture 23 - Reduction of Information Channels

Lecture 24 - Properties of Mutual Information and Introdution to Channel Capacity

Lecture 25 - Calculation of Channel Capacity for Different Information Channels

Lecture 26 - Shannon's Second Theorem

Lecture 27 - Discussion On Error Free Communication Over Noisy Channel

Lecture 28 - Error Free Communication Over A Binary Symmetric Channel and Introdution to Continous Sources and Channels

Lecture 29 - Differential Entropy and Evaluation of Mutual Information for Continuous Sources and Channels

Lecture 30 - Channel Capacity of A BandLimited Continuous Channel

Lecture 31 - Introduction to Rate-Distortion Theory

Lecture 32 - Definition and Properties of Rate-Distortion Functions

Lecture 33 - Calculation of Rate-Distortion Functions

Lecture 34 - Computational Approach for Calculation of Rate-Distortion Functions

Lecture 35 - Introdution to Quantization

Lecture 36 - Lloyd-Max Quantizer

Lecture 37 - Companded Quantization

Lecture 38 - Variable Length Coding and Problem Solving in Quantizer Design

Lecture 39 - Vector Quantization

Lecture 40 - Transform Coding - Part-I

Lecture 41 - Transform Coding - Part-II