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Information Theory and Network Coding

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Cover of 'Information Theory and Network Coding'

Table of Contents

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    Book Overview
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    Chapter 1 The Science of Information
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    Chapter 2 Information Measures
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    Chapter 3 Information Measures
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    Chapter 4 Zero-Error Data Compression
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    Chapter 5 Weak Typicality
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    Chapter 6 Strong Typicality
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    Chapter 7 Discrete Memoryless Channels
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    Chapter 8 Rate-Distortion Theory
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    Chapter 9 The Blahut–Arimoto Algorithms
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    Chapter 10 Differential Entropy
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    Chapter 11 Continuous-Valued Channels
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    Chapter 12 Markov Structures
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    Chapter 13 Information Inequalities
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    Chapter 14 Shannon-Type Inequalities
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    Chapter 15 Beyond Shannon-Type Inequalities
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    Chapter 16 Entropy and Groups
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    Chapter 17 Introduction
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    Chapter 18 The Max-Flow Bound
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    Chapter 19 Single-Source Linear Network Coding: Acyclic Networks
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    Chapter 20 Single-Source Linear Network Coding: Cyclic Networks
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    Chapter 21 Multi-source Network Coding
Attention for Chapter 10: Differential Entropy
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