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A learning algorithm to obtain self-organizing maps using fixed neighbourhood Kohonen networks

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Book cover New Trends in Neural Computation (IWANN 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 686))

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Abstract

In this paper, a learning algorithm that leads to an efficient self-organization in a Kohonen Neural Network (KNN) with fixed neighbourhood is presented. This algorithm may be faster than the originally proposed for KNNs, produces in general better covering of the input stimulus space, and can be more easily implemented in hardware due to the fixed neighbourhood it manages.

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References

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Authors and Affiliations

  1. Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Spain

    P Martin-Smith, F. J. Pelayo, A Diaz, J. Ortega & A. Prieto

Authors
  1. P Martin-Smith
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  2. F. J. Pelayo
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  3. A Diaz
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  4. J. Ortega
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  5. A. Prieto
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José Mira Joan Cabestany Alberto Prieto

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© 1993 Springer-Verlag Berlin Heidelberg

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Martin-Smith, P., Pelayo, F.J., Diaz, A., Ortega, J., Prieto, A. (1993). A learning algorithm to obtain self-organizing maps using fixed neighbourhood Kohonen networks. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_163

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  • DOI: https://doi.org/10.1007/3-540-56798-4_163

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56798-1

  • Online ISBN: 978-3-540-47741-9

  • eBook Packages: Springer Book Archive

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