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| Preface Introduction Part 1 Information Theory Chapter 1 Entropy 1.1 Entropy of a Source The Entropy Function H p1, ... , pn The Units of Entropy The Entropy of a Random Variable; Joint Entropy 1.2 Properties of Entropy Tile Range of the Entropy Function A Grouping Axiom for Entropy Properties of Joint Entropy The Convexity of the Entropy Function Entropy as an Expected Value 1.3 Additional Propcrtles of Entropy The Entropy of Countably Infinite Distributions Typical Sequences Chapter 2 Noiseless Coding 2.1 Variable Length Encoding Strings and Codes Average Codeword Length Fixed and Variable Length Codes Unique Decipherability Instantaneous Codes; The Prefix Property Kraft''s Theorem McMillan''s Theorem 2.2 Huffman Encoding An Example of Huffman Encoding Motivation for the General Case The General Case Huffman''s Algorithm 2.3 The Noiseless Coding Theorem Extensions of a Source Chapter 3 Noisy Coding 3.1 The Discrete Memoryless Channel and C |
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