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Advanced Information Theory notes
This book contains following contents: Information Theory for Discrete Variables, Information Theory for Continuous Variables, Channel Coding, Typical Sequences and Sets, Lossy Source Coding, Distributed Source Coding, Multiaccess Channels.
Author(s): Prof Dr. sc. techn. Gerhard Kramer
180 Pages 
An introduction to information Theory and Entropy
This note covers Measuring complexity, Some probability ideas, Basics of information theory, Some entropy theory, The Gibbs inequality, A simple physical example Shannon’s communication theory, Application to Biology, Examples using Bayes Theorem, Analog channels, A Maximum Entropy Principle, Application to Physics(lasers), Kullback-Leibler information measure.
Author(s): Tom Carter
139 Pages
Advanced Information Theory notes
This book contains following contents: Information Theory for Discrete Variables, Information Theory for Continuous Variables, Channel Coding, Typical Sequences and Sets, Lossy Source Coding, Distributed Source Coding, Multiaccess Channels.
Author(s): Prof Dr. sc. techn. Gerhard Kramer
180 Pages
Information Theory Lecture Notes
This PDF covers the following topics related to Information Theory : Introduction, Entropy, Relative Entropy, and Mutual Information, Asymptotic Equipartition Properties, Communication and Channel Capacity, Method of Types, Conditional and Joint Typicality, Lossy Compression & Rate Distortion Theory, Joint Source Channel Coding.
Author(s): Prof. Tsachy Weissman
75 Pages
Information Theory by Y. Polyanskiy
This PDF covers the following topics related to Information Theory : Information measures, Lossless data compression, Binary hypothesis testing, Channel coding, Lossy data compression, Advanced topics.
Author(s): Y. Polyanskiy, Y. Wu
295 Pages
Information Theory in Computer Science
This note explains the following topics: Shearer's Lemma, Entropy, Relative Entropy, Hypothesis testing, total variation distance and Pinsker's lemma, Stability in Shearer's Lemma, Communication Complexity, Set Disjointness, Direct Sum in Communication Complexity and Internal Information Complexity, Data Structure Lower Bounds via Communication Complexity, Algorithmic Lovasz Local Lemma, Parallel Repetition Theorem, Graph Entropy and Sorting.
Author(s): Madhu Sudan
NA Pages
Information Theory Lecture Notes
This is a graduate-level introduction to mathematics of information theory. This note will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.
Author(s): Prof. Yury Polyanski
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