# Introduction

Chapter

## Abstract

(1.1.1) Definition An (n,M,d) code is a set of M binary vectors of length n, called **codewords**, such that any two codewords differ in at least d places. n is called the (**block**) **length** of the code, and d is the **minimum distance** of the code. R = log_{2} M/n is called the **rate** of the code, for reasons we shall see in §§2.

## Keywords

Projective Plane Linear Code Weight Enumerator Bell System Technical Journal Goppa Code
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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## References

## Books on coding theory

- [1]E.R. Berlekamp, Algebraic Coding Theory, McGraw-Hill, New York, 1968. ( The best book available. Excellent treatment of BCH codes. )Google Scholar
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## Periodicals The first three

- [9]IEEE (Institute of Electrical and Electronic Engineers) Transactions on Information Theory (abbreviated PGIT)Google Scholar
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- [11]Problemy Peredachi Informatsii (Russian, abbreviated PPI), are the main sources for papers on coding theory. Occasional articles on coding theory will be found inGoogle Scholar
- [12]] IEE Transactions on Communications (Abbreviated PGCOM) (See in 1971).Google Scholar
- [13]Discrete Mathematics (abbreviated DM. See e.g., the special issue on coding theory, September 1972.)Google Scholar
- [14]IBM Journal of Research and Development, (abbreviated IBMJ) (See e.g., the special issue on coding theory, July 1970.)Google Scholar
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- [16]Journal of Combinatorial Theory, (abbreviated JCT).Google Scholar

## Books on Communication Theory

- ] R.G. Gallager, Information Theory and Reliable Communication, Wiley, New York, 1969.Google Scholar
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- [19]Toby Berger, Rate Distortion Theory, Prentice-Hall, Englewood Cliffs, New York, 1971.Google Scholar
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- [22]F. Jelinek, Probabilistic Information Theory, McGraw-Hill, N.Y., 1968. ( Very thorough, advanced treatment of information theory. )MATHGoogle Scholar

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© Springer-Verlag Wien 1975