- 信息论的信息谱方法(英文版香农信息科学经典)
- - 作者：(日)韩太舜|责编:陈亮//刘叶青
  - 出版社：世图出版公司
  - ISBN：9787519296896
  - 出版日期：2023/01/01
  - 页数：538
- 售价：51.6

内容大纲
本书聚焦于任意非平稳和/或附带任意大写字母的非遍历源和通道，很好地补充了现有文献在信息论和编码理论方面内容的不足。本书特色有三：一是别具特色的讲述方式——虽然内容主题比较常见，但作者在阐述各种概念定理时采用了非传统的方式，让人眼前一亮。二是作者广阔的知识面和独特的思维为许多问题提供了新的见解，富有原创性。此外，本书内容丰富详实，还包含了相当多的历史评论和大量的参考书目，为读者进一步阅读拓展知识面提供了参考书目。
作者介绍
目录
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

内容大纲

作者介绍

目录

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