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Kohonen neural networks: A parallel algorithm for automatic signal reconstruction

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High-Performance Computing and Networking (HPCN-Europe 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 919))

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Abstract

A general purpose method for data modeling based on self-adapting Kohonen neural network has been presented. The method has been efficiently implemented on MIMD distributed memory machines. Future works concern the choice of different learning functions. A new, partially asynchronous, implementation is under development.

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References

  1. T.Kohonen, “Self-organization and associative memory”, Springer-Verlag, Berlin, 1988

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  2. J.Kangas, T.Kohonen, J.Laaksonen “Variants of self-organizing maps”, IEEE Trans. on Neural Net., Vol. 1, N. 1, March 1990

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  3. P.Flatt, A.Karp, “Measuring Parallel Processor Performance”, Comm. ACM (33), pp. 539–543, 1990

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  4. R.Devaney, “Caos and Fractals”, Addison-Welsey, 1990

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Authors and Affiliations

  1. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Piazza Leonardo da Vinci, 32, I20133, Milano, Italy

    Paolo Cremonesi

Authors
  1. Paolo Cremonesi
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Bob Hertzberger Giuseppe Serazzi

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© 1995 Springer-Verlag Berlin Heidelberg

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Cremonesi, P. (1995). Kohonen neural networks: A parallel algorithm for automatic signal reconstruction. In: Hertzberger, B., Serazzi, G. (eds) High-Performance Computing and Networking. HPCN-Europe 1995. Lecture Notes in Computer Science, vol 919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046742

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  • DOI: https://doi.org/10.1007/BFb0046742

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59393-5

  • Online ISBN: 978-3-540-49242-9

  • eBook Packages: Springer Book Archive

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