杨伟豪编著的《信息论基础(英文版)》原版自2002年出版以来，被哥伦比亚大学、康奈尔大学、麻省理工学院、斯坦福大学等美国著名学府所采用，是信息理论方面的重要教材。本书首先介绍了信息论的经典内容，然后全面详细地论述了，一度量、网络编码、Shannon型与非Shannon型信息不等式等理论，以及熵函数与群论之间的关系。书中配有大量的实例、插图和习题，适合作为通信、电子信息、计算机等专业的高年级本科生和研究生的教材。也可供相关领域的科研人员参考。

《信息论基础(英文版)》作者（杨伟豪）现为香港中文大学网络编码研究所主任，是网络编码理论的提出者之一。本书原版自2002年出版以来，被哥伦比亚大学、康奈尔大学、麻省理工学院、斯坦福大学等美国著名学府所采用，是信息理论方面的重要教材。本书首先介绍了信息论的经典内容，然后全面详细地论述了，度量、网络编码、Shannon型与非Shannon型信息不等式等理论，以及熵函数与群论之间的关系。《信息论基础(英文版)》中配有大量的实例、插图和习题，适合作为通信、电子信息、计算机等专业的高年级本科生和研究生的教材，也可供相关领域的科研人员参考。

1. THE SCIENCE OF INFORMATION

2. INFORMATION MEASURES

2.1 Independence and Markov Chains

2.2 Shannon's Information Measures

2.3 Continuity of Shannon's Information Measures

2.4 Chain Rules

2.5 Informational Divergence

2.6 The Basic Inequalities

2.7 Some Useful Information Inequalities

2.8 Fano's Inequality

2.9 Entropy Rate of Stationary Source

Problems

Historical Notes

3. ZERO-ERROR DATA COMPRESSION

3.1 The Entropy Bound

3.2 Prefix Codes

 3.2.1 Definition and Existence

 3.2.2 Huffman Codes

3.3 Redundancy of Prefix Codes

Problems

Historical Notes

4. WEAK TYPICALITY

4.1 The Weak AEP

4.2 The Source Coding Theorem

4.3 Efficient Source Coding

4.4 The Shannon-McMiilan-BreimanTheorem

Problems

Historical Notes

5. STRONG TYPICALITY

5.1 StrongAEP

5.2 Strong Typicality Versus Weak Typicality

5.3 Joint Typicality

5.4 An Interpretation of the Basic Inequalities

Problems

Historical Notes

6. THE/-MEASURE

6.1 Preliminaries

6.2 The/-Measure for Two Random Variables

6.3 Construction of the/-Measure ч*

6.4 #* Can be Negative

6.5 Information Diagrams

6.6 Examples of Applications

Appendix 6.A: A Variation of the Inclusion-Exclusion Formula

Problems

Historical Notes

7. MARKOV STRUCTURES

7.1 Conditional Mutual Independence

7.2 Full Conditional Mutual Independence

7.3 Markov Random Field

7.4 Markov Chain

Problems

Historical Notes

8. CHANNEL CAPACITY

8.1 Discrete MemorylessChannels

8.2 The Channel Coding Theorem

8.3 The Converse

8.4 Achievability of the Channel Capacity

8.5 A Discussion

8.6 Feedback Capacity

8.7 Separation of Source and Channel Coding

Problems

Historical Notes

9. RATE-DISTORTION THEORY

9.1 Single-Letter Distortion Measures

9.2 The Rate-Distortion Function R(D)

9.3 The Rate-Distortion Theorem

9.4 The Converse

9.5 Achievability of RI(D)

Problems

Historical Notes

10. THE BLAHUT-ARIMOTO ALGORITHMS

10.I Alternating Optimization

10.2 The Algorithms

 10.2.1 Channel Capacity

 10.2.2 The Rate-Distortion Function

10.3 Convergence

 10.3.1- A Sufficient Condition

 10.3.2 Convergence to the Channel Capacity

Problems

Historical Notes

11. SINGLE-SOURCE NETWORK CODING

11.1 A Point-to-Point Network

11.2 What is Network Coding?

11.3 A Network Code

11.4 The Max-Flow Bound

11.5 Achievability of the Max-Flow Bound

 11.5.1 Acyclic Networks

 11.5.2 Cyclic Networks

Problems

Historical Notes

12. INFORMATION INEQUALITIES

12.1 The Region Fn

12.2 Information Expressions in Canonical Form

12.3 A Geometrical Framework

 12.3.1 Unconstrained Inequalities

 12.3.2 Constrained Inequalities

 12.3.3 Constrained Identities

12.4 Equivalence of Constrained Inequalities

12.5 The Implication Problem of Conditional Independence

Problems

Historical Notes

13 SHANNON-TYPE INEQUALITIES

13.1 The Elemental Inequalities

13.2 A Linear Programming Approach

 13.2.1 Unconstrained Inequalities

 13.2.2 Constrained Inequalities and Identities

13.3 A Duality

13.4 Machine Proving - ITIP

13.5 Tackling the Implication Problem

13.6 Minimality of the Elemental Inequalities

Appendix 13.A: The Basic Inequalities and the Polymatroidal

 Axioms

Problems

Historical Notes

14. BEYOND SHANNON-TYPE INEQUALITIES

14.1 Characterizations of г2,г3, and гn

14.2 A Non-Shannon-Type Unconstrained Inequality

14.3 A Non-Shannon-Type Constrained Inequality

14.4 Applications

Problems

Historical Notes

15. MULTI-SOURCE NETWORK CODING

15.1 Two Characteristics

 15.1.1 The Max-Flow Bounds

 15.1.2 Superposition Coding

15.2 Examples of Application

 15.2.1 Multilevel Diversity Coding

 15.2.2 Satellite Communication Network

15.3 A Network Code for Acyclic Networks

15.4 An Inner Bound

15.5 An Outer Bound

15.6 The LP Bound and Its Tightness

15.7 Achievability of Rin

Appendix 15.A: Approximation of Random Variables with

 Infinite Alphabets

Problems

Historical Notes

16. ENTROPY AND GROUPS

16.1 Group Preliminaries

16.2 Group-Characterizable Entropy Functions

16.3 A Group Characterization of гn

16.4 Information Inequalities and Group Inequalities

Problems

Historical Notes

Bibliography

Index