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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 Rate-Distortion Analysis of Symmetric Remote Gaussian Source Coding: Centralized Encoding vs. Distributed Encoding, Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling, Robust Baseband Compression Against Congestion in Packet-Based Fronthaul Networks Using Multiple Description Coding, Amplitude Constrained MIMO Channels: Properties of Optimal Input Distributions and Bounds on the Capacity, Quasi-Concavity for Gaussian Multicast Relay Channels, Gaussian Multiple Access Channels with One-Bit Quantizer at the Receiver, Efficient Algorithms for Coded Multicasting in Heterogeneous Caching Networks, Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks, Symmetry, Outer Bounds, and Code Constructions: A Computer-Aided Investigation on the Fundamental Limits of Caching.
Author(s): Shlomo Shamai, Abdellatif Zaidi
296 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 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 Rate-Distortion Analysis of Symmetric Remote Gaussian Source Coding: Centralized Encoding vs. Distributed Encoding, Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling, Robust Baseband Compression Against Congestion in Packet-Based Fronthaul Networks Using Multiple Description Coding, Amplitude Constrained MIMO Channels: Properties of Optimal Input Distributions and Bounds on the Capacity, Quasi-Concavity for Gaussian Multicast Relay Channels, Gaussian Multiple Access Channels with One-Bit Quantizer at the Receiver, Efficient Algorithms for Coded Multicasting in Heterogeneous Caching Networks, Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks, Symmetry, Outer Bounds, and Code Constructions: A Computer-Aided Investigation on the Fundamental Limits of Caching.
Author(s): Shlomo Shamai, Abdellatif Zaidi
296 Pages
Information Theory and Coding cam
The PDF covers the following topics related to Information Theory : Foundations: probability, uncertainty, information, Entropies defined, and why they are measures of information, Source coding theorem; prefix, variable-, and fixed-length codes, Channel types, properties, noise, and channel capacity, Continuous information, density, noisy channel coding theorem, Fourier series, convergence, orthogonal representation, Useful Fourier theorems, transform pairs, Sampling, aliasing, Discrete Fourier transform, Fast Fourier Transform Algorithms, The quantised degrees-of-freedom in a continuous signal, Gabor-Heisenberg-Weyl uncertainty relation, Kolmogorov complexity.
Author(s): J G Daugman
75 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
This note will explore the basic concepts of information theory. It is highly recommended for students planning to delve into the fields of communications, data compression, and statistical signal processing. Topics covered includes: Entropy and mutual information, Chain rules and inequalities, Data processing, Fano's inequality, Asymptotic equipartition property, Entropy rate, Source coding and Kraft inequality, Optimal code length and roof code, Huffman codes, Shannon-Fano-Elias and arithmetic codes, Maximum entropy, Channel capacity, Channel coding theorem, Differential entropy, Gaussian channel, Parallel Gaussian channel and water-filling, Quantization and rate-distortion.
Author(s): Yao Xie
NA Pages
Information Theory, Inference, and Learning Algorithms (David J.C. MacKay)
Currently this section contains no detailed description for the page, will update this page soon.
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