信息論與編碼（英文版）

Chapter 1 Introduction
Contents
Before it starts, there is something must be known
　1.1 What is Information
　1.2 What’s Information Theory？
　　1.2.1 Origin and Development of Information Theory
　　1.2.2 The application and achievement of Information Theory methods
　1.3 Formation and Development of Information Theory
　Questions and Exercises
　Biography of Claude Elwood Shannon
Chapter 2 Basic Concepts of Information Theory
　Contents
　Preparation knowledge
　2.1 Self-information and conditional self-information
　　2.1.1 Self-Information
　　2.1.2 Conditional Self-Information
　2.2 Mutual information and conditional mutual information
　2.3 Source entropy
　　2.3.1 Introduction of entropy
　　2.3.2 Mathematics description of source entropy
　　2.3.3 Conditional entropy
　　2.3.4 Union entropy （Communal entropy）
　　2.3.5 Basic nature and theorem of source entropy
　2.4 Average mutual information
　　2.4.1 Definition
　　2.4.2 Physics significance of average mutual information
　　2.4.3 Properties of average mutual information
　2.5 Continuous source
　　2.5.1 Entropy of the continuous source （also called differential entropy）
　　2.5.2 Mutual information of the continuous random variable
　Questions and Exercises
　Additional reading materials
Chapter 3 Discrete Source Information
　Contents
　3.1 Mathematical model and classification of the source
　3.2 The discrete source without memory
　3.3 Multi-marks discrete steady source
　3.4 Source entropy of discrete
　　4.2.4 Relationship between entropy, channel doubt degree and mutual information
　4.3 The discrete channel without memory and its channel capacity
　4.4 Channel capacity
　　4.4.1 Concept of channel capacity
　　4.4.2 Discrete channel without memory and its channel capacity
　　4.4.3 Continuous channel and its channel capacity
Chapter 5 kossless source coding
　Contents
　5.1 Lossless coder
　5.2 Lossless source coding
　　5.2.1 Fixed length coding theorem
　　5.2.2 Unfixed length source coding
　5.3 Lossless source coding theorems
　　5.3.1 Classification of code and main coding method
　　5.3.2 Kraft theorem
　　5.3.3 Lossless unfixed source coding theorem （Shannon First theorem）
　5.4 Pragmatic examples of lossless source coding
　　5.4.1 Huffman coding
　　5.4.2 Shannon coding and Fano coding
　5.5 The Lempel-ziv algorithm
　5.6 Run-Length Encoding and the PCX format
　Questions and Exercises
Chapter 6 Limited distortion source coding
　Contents
　6.1 The start point of limit distortion theory
　6.2 Distortion measurement
　　6.2.1 Distortion function
　　6.2.2 Average distortion
　6.3 Information rate distortion function
　6.4 Property of R（D）
　　6.4.1 Minimum of D and R（D）
　　6.4.2 Dmax and R（Dmax）
　　6.4.3 The under convex function of R（D）
　　6.4.4
　Questions and exercises
Bibliography