Introduction to coding and information theory
著者
書誌事項
Introduction to coding and information theory
（Undergraduate texts in mathematics）
Springer, c1997
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.
目次
- Introduction: Preliminaries
- Miscellany
- Some Probability
- Matrices 1. An Introduction to Codes Strings and Things
- What are codes? Uniquely Decipherable Codes
- Instantaneous Codes and Kraft's Theorem 2. Efficient Encoding Information Sources
- Average Codeword Length
- Huffman Encoding
- The Proof that Huffman Encoding is the Most Efficient 3. Noiseless Coding Entropy
- Properties of Entropy
- Extensions of an Information 1= Source
- The Noiseless Coding Theorem II Coding Theory 4. The Main Coding Theory Problem Communications Channels
- Decision Rules
- Nearest Neighbor Decoding
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