1 Source Coding 1.1 Source Coding: Fixed-Length Codes 1.2 Source Coding: Variable-Length Codes 1.3 Coding for General Sources: Fixed-Length Codes 1.4 Fixed-Length Coding for Mixed Sources 1.5 Strong Converse Theorem for Source Coding 1.6 ε-Source Coding 1.7 Coding for General Sources: Variable-Length Codes 1.8 Coding for General Source: Weak Variable-Length Codes 1.9 Source Coding and Large Deviation: Decoding Error Probability 1.10 Source Coding and Large Deviation: Probability of Correct Decoding 1.11 Reliability Functions of the General Source with Variable-Length Coding 1.12 Information Spectrum and Invariancy 2 Random Number Generation 2.1 Random Number Generation 2.2 Resolvability and Intrinsic Randomness 2.3 Strong Converse Theorem for Random Number Generation 2.4 δ-Random Number Generation 2.5 Variable-Length Intrinsic Randomness 2.6 Random Number Generation and Source Coding 3 Channel Coding 3.1 Channel Coding: Stationary Memoryless Channel 3.2 Coding for General Channel 3.3 Coding for Mixed Channels 3.4 ε-Channel Coding 3.5 Strong Converse Theorem on Channel Coding 3.6 Channel Capacity with Cost Constraint 3.7 Strong Converse Property of Channel with Cost Constraint 3.8 Joint Source-Channel Coding 3.9 Separation Theorems of the Traditional Type 4 Hypothesis Testing 4.1 Hypothesis Testing 4.2 ε-Hypothesis Testing 4.3 Strong Converse Theorem for Hypothesis Testing 4.4 Hypothesis Testing and Large Deviation Probability ofTesting Error 4.5 Hypothesis Testing and Large Deviation: Probability ofCorrect Testing 4.6 Generalized Hypothesis Testing 4.7 Hypothesis Testing and Source Coding 5 Rate-Distortion Theory 5.1 Coding Subject to Distortion Criterion 5.2 Rate-Distortion Theory for Stationary Memoryless Sources 5.3 General Rate-Distortion Theory 5.4 Rate-Distortion Function Rfm(D|X) 5.5 Rate-Distortion Function Rfa(D|X) 5.6 Rate-Distortion Function Rum(D|X) 5.7 Rate-Distortion Function Rua(D|X) 5.8 Rate-Distortion for Stationary Memoryless Sources Revisited 5.9 Rate-Distortion for Stationary Ergodic Sources 5.10 Rate-Distortion Function for Mixed Sources 6 Identification Code and Channel Resolvability
6.1 Identification Code and Channel Resolvability 6.2 Identification Coding 6.3 Channel Resolvability 6.4 Identification Capacity Theorem and Channel Resolvability Theorem 6.5 Identification Capacity with Cost Constraint 6.6 Channel Resolvability with Cost Constraint 6.7 Identification Capacity and Resolvability of Continuous Input Channels 6.8 Identification-Transmission Codes 7 Multi-Terminal Information Theory 7.1 What Is Multi-Terminal Information Theory? 7.2 The Slepian-Wolf Source Coding System 7.3 Slepian-Wolf Source Coding for Mixed Sources 7.4 ε-Source Coding for Slepian-Wolf Source Coding System 7.5 Strong Converse Theorem for Slepian-Wolf Source Coding System 7.6 Multiple-Access Channel Coding Systems 7.7 General Capacity Region Theorem for Multiple-AccessChannels 7.8 Stationary Memoryless Multiple-Access Channels 7.9 Mixed Multiple-Access Channels 7.7.1 7.11 ε-Coding for Multiple-Access Channel 7.12 Strong Converse Theorem for Multiple-Access Channels 7.13 Multiple-Access Channels with Cost Constraint References Index
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