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Algorithmic issues in coding theory

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Book cover Foundations of Software Technology and Theoretical Computer Science (FSTTCS 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1346))

Abstract

The goal of this article is to provide a gentle introduction to the basic definitions, goals and constructions in coding theory. In particular we focus on the algorithmic tasks tackled by the theory. We describe some of the classical algebraic constructions of error-correcting codes including the Hamming code, the Hadamard code and the Reed Solomon code. We describe simple proofs of their error-correction properties. We also describe simple and efficient algorithms for decoding these codes. It is our aim that a computer scientist with just a basic knowledge of linear algebra and modern algebra should be able to understand every proof given here. We also describe some recent developments and some salient open problems.

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References

  1. S. Ar, R. Lipton, R. Rubinfeld and M. Sudan. Reconstructing algebraic functions from mixed data. SIAM Journal on Computing, to appear. Preliminary version in Proceedings of the 33rd Annual IEEE Symposium on Foundations of Computer Science, pp. 503–512, 1992.

    Google Scholar 

  2. E. R. Berlekamp. Algebraic Coding Theory. McGraw Hill, New York, 1968.

    Google Scholar 

  3. E. R. Berlekamp. Bounded Distance +1 Soft-Decision Reed-Solomon Decoding. In IEEE Transactions on Information Theory, pages 704–720, vol. 42, no. 3, May 1996.

    Article  MATH  Google Scholar 

  4. E. R. Berlekamp, R. J. McEliece and H. C. A. van Tilborg. On the inherent intractability of certain coding problems. IEEE Transactions on Information Theory, 24:384–386, 1978.

    Article  MATH  Google Scholar 

  5. R. DeMello and R. Lipton. A probabilistic remark on algebraic program testing. Information Processing Letters, 7(4):193–195, June 1978.

    Article  Google Scholar 

  6. O. Goldreich, R. Rubinfeld and M. Sudan. Learning polynomials with queries: The highly noisy case. Proceedings of the 36th Annual IEEE Symposium on Foundations of Computer Science, pp. 294–303, 1995.

    Google Scholar 

  7. D. Grigoriev. Factorization of Polynomials over a Finite Field and the Solution of Systems of Algebraic Equations. Translated from Zapiski Nauchnykh Seminarov Lenningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova AN SSSR, Vol. 137, pp. 20–79, 1984.

    Google Scholar 

  8. E. Kaltofen. A Polynomial-Time Reduction from Bivariate to Univariate Integral Polynomial Factorization. In 23rd Annual Symposium on Foundations of Computer Science, pages 57–64, 1982.

    Google Scholar 

  9. E. Kaltofen. Polynomial factorization 1987–1991. LATIN '92, I. Simon (Ed.) Springer LNCS, v. 583:294–313, 1992.

    Google Scholar 

  10. R. Lidl and H. Niederreiter. Introduction to Finite Fields and their Applications. Cambridge University Press, 1986

    Google Scholar 

  11. F. J. MacWilliams and N. J. A. Sloane. The Theory of Error-Correcting Codes. North-Holland, Amsterdam, 1981.

    Google Scholar 

  12. J. Radhakrishnan. Personal communication, January, 1996.

    Google Scholar 

  13. J. T. Schwartz. Fast probabilistic algorithms for verification of polynomial identities. Journal of the ACM, 27(4):701–717, 1980.

    Article  MATH  Google Scholar 

  14. M. Sipser and D. A. Spielman. Expander codes. IEEE Transactions on Information Theory, 42(6):1710–1722, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  15. D. A. Spielman. Linear-time encodable and decodable error-correcting codes. IEEE Transactions on Information Theory, 42(6):1723–1731, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  16. M. Sudan. Decoding of Reed Solomon codes beyond the error-correction bound. Journal of Complexity, 13(1):180–193, March 1997. See also http://theory.lcs.mit.edu/~madhu/papers.html for a more recent version.

    Article  MATH  MathSciNet  Google Scholar 

  17. J. H. van Lint. Introduction to Coding Theory. Springer-Verlag, New York, 1982.

    Google Scholar 

  18. A. Vardy. Algorithmic complexity in coding theory and the minimum distance problem. Proceedings of the Twenty-Ninth Annual ACM Symposium on Theory of Computing, pp. 92–109, 1997.

    Google Scholar 

  19. B. L. van der Waerden. Algebra, Volume 1. Frederick Ungar Publishing Co., Inc., page 82.

    Google Scholar 

  20. L. Welch and E. R. Berlekamp. Error correction of algebraic block codes. US Patent Number 4,633,470, issued December 1986.

    Google Scholar 

  21. R. E. Zippel. Probabilistic algorithms for sparse polynomials. EUROSAM '79, Lecture Notes in Computer Science, 72:216–226, 1979.

    MATH  MathSciNet  Google Scholar 

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S. Ramesh G Sivakumar

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© 1997 Springer-Verlag Berlin Heidelberg

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Sudan, M. (1997). Algorithmic issues in coding theory. In: Ramesh, S., Sivakumar, G. (eds) Foundations of Software Technology and Theoretical Computer Science. FSTTCS 1997. Lecture Notes in Computer Science, vol 1346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0058031

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  • DOI: https://doi.org/10.1007/BFb0058031

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63876-6

  • Online ISBN: 978-3-540-69659-9

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