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Neural networks as error correcting systems in digital communications

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Artificial Neural Networks (IWANN 1991)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 540))

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Abstract

Feed forward neural network are very powerful devices for soft-decision decoding of linear block codes. A practical realization for a (7,4) BCH code is presented. The relationship between maximum likelihood decoding, winner-takes-all neural networks and neural networks with a sigmoidal response function is established. It is shown how learning with an error back propagation algorithm can drastically improved the performance of the decoding network in the case of an additive gaussian channel with memory.

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References

  1. E.C. Posner, ”Neural Networks in Communication”, IEEE Trans. on Neural Networks, vol. 1, no. 1, 1990.

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  2. F.J. MacWilliams and N.J.A. Sloane, The Theory of Error correcting Codes. North-Holland, 2nd reprint 1983.

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  3. S. Benedetto, E. Bigliari, and V. Castellani, Digital Transmission Theory, Prentice-Hall, Inc. Englewood Cliffs, New Jersey, 1988.

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  4. A. Viterbi and J.K. Omura, Principles of Digital Communication and Coding. McGraw-Hill 1979.

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Author information

Authors and Affiliations

  1. Departamento de Informática, Universidad Autónoma de Barcelona, 08193, Barcelona, Spain

    I. Ortuño

  2. Departamento de Física, Universidad de Murcia, 30.071, Murcia, Spain

    M. Ortuño

  3. Departamento de Teoría de la señal y Comunicación, Universidad Politécnica de Cataluña, 08034, Barcelona, Spain

    J. A. Delgado

Authors
  1. I. Ortuño
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  2. M. Ortuño
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  3. J. A. Delgado
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Editor information

Alberto Prieto

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© 1991 Springer-Verlag Berlin Heidelberg

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Ortuño, I., Ortuño, M., Delgado, J.A. (1991). Neural networks as error correcting systems in digital communications. In: Prieto, A. (eds) Artificial Neural Networks. IWANN 1991. Lecture Notes in Computer Science, vol 540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035921

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  • DOI: https://doi.org/10.1007/BFb0035921

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54537-8

  • Online ISBN: 978-3-540-38460-1

  • eBook Packages: Springer Book Archive

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