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A Short Course in Information Theory (D. MacKay)

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A Short Course in Information Theory (D. MacKay)

A Short Course in Information Theory (D. MacKay)

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Lecture Notes On Information Theory

Lecture Notes On Information Theory

These notes provide a graduate-level introduction to the mathematics of Information Theory. Topics covered includes: Information measures: entropy, divergence and mutual information, Sufficient statistic, Extremization of mutual information, Lossless data compression, Channel coding, Linear codes, Lossy data compression, Applications to statistical decision theory, Multiple-access channel, Entropy method in combinatorics and geometry.

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Information Theory by Yao Xie

Information Theory by Yao Xie

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.

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A Discipline Independent Definition of Information (Robert M. Losee)

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An Introduction to Information Theory and Entropy (Tom Carter)

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