Coding and information theory
Author(s)
Bibliographic Information
Coding and information theory
（Graduate texts in mathematics, 134）
Springer-Verlag, c1992
- : us
- : gw
Available at / 138 libraries
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University of Tsukuba Library, Library on Library and Information Science
: us007.1:R-66931004860
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Hiroshima University Central Library, Interlibrary Loan
: New York007.1:R-66/HL2530002500404526
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Hokkaido University, Library, Graduate School of Science, Faculty of Science and School of Science図書
dc20:003/r6612070230247
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Note
Bibliographical references: p. [475]-477
Includes indexes
Description and Table of Contents
- Volume
-
: us ISBN 9780387978123
Description
This book is an introduction to information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and modern algebra, but is otherwise self- contained. The intent is to describe as clearly as possible the fundamental issues involved in these subjects, rather than covering all aspects in an encyclopedic fashion. The first quarter of the book is devoted to information theory, including a proof of Shannon's famous Noisy Coding Theorem. The remainder of the book is devoted to coding theory and is independent of the information theory portion of the book. After a brief discussion of general families of codes, the author discusses linear codes (including the Hamming, Golary, the Reed-Muller codes), finite fields, and cyclic codes (including the BCH, Reed-Solomon, Justesen, Goppa, and Quadratic Residue codes). An appendix reviews relevant topics from modern algebra.
Table of Contents
1: Entropy. 2: Noisless Coding. 3: Noisy Coding. 4: General Remarks on Codes. 5: Linear Codes. 6: Some Linear Codes. 7: Finite Fields and Cyclic Codes. 8: Some Cyclic Codes.
- Volume
-
: gw ISBN 9783540978121
Description
This text is an introduction to the subjects of information and coding theory at the graduate or advanced undergraduate level. It assumes a basic knowledge of probability and linear algebra, but is otherwise self-contained. The first quarter of the book is devoted to the basics of information theory, including a proof of Shannon's famous Noisy Coding Theorem. The remainder of the book is devoted to coding theory and has a decidedly algebraic flavour. After a brief discussion of general families of codes, the authors discuss linear codes, (including the Hamming, Golay, and Reed-Miller codes), finite fields and cyclic codes. An appendix reviews relevant topics from modern algebra.
Table of Contents
1: Entropy. 2: Noisless Coding. 3: Noisy Coding. 4: General Remarks on Codes. 5: Linear Codes. 6: Some Linear Codes. 7: Finite Fields and Cyclic Codes. 8: Some Cyclic Codes.
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