An Introduction to Information Theory and Applications
This note explains the following topics, uncertainty and information, Efficient coding of information, Stationary processes and markov chains, Coding for noisy transmission, Complements to efficient coding of Information, Error correcting codes and cryptography.
Author(s): F Bavaud, J C Chappelier and J Kohlas
293 Pages
Applied Digital Information theory
This note serves as a comprehensive guide to fundamental concepts in information theory and coding. This pdf provides discrete probability theory, information theory, and coding principles. Beginning with Shannons measure of information, then delves into the efficient coding of information, the methodology of typical sequences is introduced, emphasizing the distinction between lossy and lossless source encoding. The text also discusses coding for noisy digital channels, block coding principles and tree and trellis coding principles.
Author(s): James L.Massey
153 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 Shannons communication theory, Application to Biology, Examples using Bayes Theorem, Analog channels, A Maximum Entropy Principle, Application to Physics lasers, KullbackLeibler information measure.
Author(s): Tom Carter
139 Pages
This book explains basics of thermodynamics, including thermodynamic potentials, microcanonical and canonical distributions, and evolution in the phase space, The inevitability of irreversibility, basics of information theory, applications of information theory, new second law of thermodynamics and quantum information.
Author(s): Gregory Falkovich
165 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 and Rate Distortion Theory, Joint Source Channel Coding.
Author(s): Prof. Tsachy Weissman
75 Pages
Information Theory for Data Communications and Processing
The PDF covers the following topics related to Information Theory, Information Theory for Data Communications and Processing, On the Information Bottleneck Problems, Models, Connections,Applications and Information Theoretic Views, Variational Information Bottleneck for Unsupervised Clustering, Deep Gaussian Mixture Embedding, Asymptotic RateDistortion Analysis of Symmetric Remote Gaussian Source Coding, Centralized Encoding vs. Distributed Encoding, NonOrthogonal eMBBURLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling, Robust Baseband Compression Against Congestion in PacketBased Fronthaul Networks Using Multiple Description Coding, Amplitude Constrained MIMO Channels, Properties of Optimal Input Distributions and Bounds on the Capacity, QuasiConcavity for Gaussian Multicast Relay Channels, Gaussian Multiple Access Channels with OneBit Quantizer at the Receiver, Efficient Algorithms for Coded Multicasting in Heterogeneous Caching Networks, CrossEntropy Method for Content Placement and User Association in CacheEnabled Coordinated UltraDense Networks, Symmetry, Outer Bounds, and Code Constructions, A ComputerAided Investigation on the Fundamental Limits of Caching.
Author(s): Shlomo Shamai, Abdellatif Zaidi
296 Pages
