Cover image for A student's guide to coding and information theory
A student's guide to coding and information theory
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Publication Information:
Cambridge ; New York : Cambridge University Press, c2012
Physical Description:
xiii, 191 p. : ill. ; 23 cm.

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30000010302407 Q360 M68 2012 Open Access Book Book

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This easy-to-read guide provides a concise introduction to the engineering background of modern communication systems, from mobile phones to data compression and storage. Background mathematics and specific engineering techniques are kept to a minimum so that only a basic knowledge of high-school mathematics is needed to understand the material covered. The authors begin with many practical applications in coding, including the repetition code, the Hamming code and the Huffman code. They then explain the corresponding information theory, from entropy and mutual information to channel capacity and the information transmission theorem. Finally, they provide insights into the connections between coding theory and other fields. Many worked examples are given throughout the book, using practical applications to illustrate theoretical definitions. Exercises are also included, enabling readers to double-check what they have learned and gain glimpses into more advanced topics, making this perfect for anyone who needs a quick introduction to the subject.

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Choice Review

Moser and Chen have taught in the electrical engineering department at National Chiao Tung Univ. (Taiwan) for several years, and Moser heads the information theory lab there. The authors have succeeded in writing a useful introductory text on the fundamental topics in coding and information theory. To allow for a broader readership, the presented information requires only basic probability and calculus to understand the material. The eight-chapter book covers basic coding, including simple error-detection codes, Hamming code, and Huffman code. The remainder of the work covers topics such as entropy, coding efficiency, channel capacity, information theory, and turbo coding. Each topic introduces readers to the material without relying on advanced statistics and probability. Many examples are included to illustrate the concepts. Overall, the book is an excellent introduction to the coding and information theory fields. Summing Up: Highly recommended. Students of all levels and professionals/practitioners. L. McLauchlan Texas A&M University-Kingsville

Table of Contents

1 Introduction Chung-Hsuan Wang
2 Error-detecting codes Chung-Hsuan Wang
3 Repetition and hamming codes Francis Lu
4 Data compression: efficient coding of a random message
5 Entropy and Shannon's source coding theorem
6 Mutual information and channel capacity Jwo-Yuh Wu
7 Achieving the Shannon limit by turbo coding
8 Other aspects of coding theory Francis Lu