# Coding and Information Theory

## Springer-Verlag Graduate Texts in Mathematics, Volume 134

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, Golay, and 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.

**1992, ISBN 0-387-97812-7, 486 pp., Hardcover**

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