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#### Information Theory & Coding

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Chapter 1 Introduction
Before it starts， there is something must be known
1．1 What is Information
1．2 What is Information Theory
1．2．1 The Origin and Development of lnformation Theory
1．2．2 The Application and Achievement of Information Theory Methods
1．3 Forma/ion and Development of lnformation Theory
Questions and Exercises
Biography of Claude Elwood Shannon

Chapter 2Basic Concepts of Information Theory Preparation knowledge
2．1 Self-information and conditional self-information
2．1．1 Self-information
2．1．2 ConditionalSelf-information
2．2 Mutualinformation and conditionalmutualinformation
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
2．3．5 Basic nature and theorem of source entropy
2．4 Averagemutualinformation
2．4． 1Definition
2．4．2 Physics sigriificance of average mutual information
2．4．3 Properties of average mutual Information
2．5 Continuous source
2．5．1 Entropy of the continuous source
2．5．2 Mutualinformation of the continuous random variable
2．6．1 Mathematical model and classification of the source
2．6．2 The discrete source without memo
2．6．4 Source entropy of discrete steady source and linut entropy
2．6．5 The source redundancy and the information difference
2．6．6 Markov information source

Chapter 3 Lossless source coding
3．1 Lossless coder
3．2 Lossless source coding
3．2．1 Fixedlength coding theorem
3．2．2 Unfixedlength source coding
3．3 Lossless source coding theorems
3．3．1 Classification of code and main coding method
3．3．2 Kraft theorem
3．3．3 Lossless unfixed source coding theore
3．4 Pragmatic examples of lossless source coding
3．4．1 Huffmancoding
3．4．2 Shannon coding and Fano coding
3．5 The Lempel-ziv algorithm
3．6 Run length encoding and the PCX format

Chapter 4 Limited distortion source coding
4．1 The start point of limit distortion theory
4．2 Distortion measurement
4．2．1 Distortion function
4．2．2 Average distortion
4．3 Information rate distortion function
4．4 Properties of R（D）
4．4．1 Minimum of D and R（D）
4．4．2 DraxandR（Dmax）
4．4．3 The under convex feature of R（D）
4．4．4 The decreasing feature of R（D）
4．4．5 R（D）is a continuous function of D
4．5 Calculation of R（D）
4．5．1 Calculation of R（D）of binary symmetric source
4．5．2 Calculation of R（D）of Gauss source
4．6 Limited distortion source encoding theorem
……

Chapter 5 Channel Capacity and Channel Coding

Bibliography

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