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Comparative Analysis of Learning Methods of Cellular-Neural Associative Memory

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Parallel Computing Technologies (PaCT 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1662))

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Abstract

In this paper various methods of CNAM learning (synthesis) are compared in order to find their common features. This allows to transfer the important characteristics among the methods, and to do some assumptions about their capabilities. Also the influence of learning parameters in some methods on the CNAM stability is investigated, and recommendations on their choice are given.

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Author information

Authors and Affiliations

  1. Supercomputer Software Department, ICMMG of Siberian Branch, Russian Academy of Science, Pr. Lavrentieva, 6, Novosibirsk, 630090, Russia

    Sergey Pudov

Authors
  1. Sergey Pudov
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Editor information

Editors and Affiliations

  1. Computing Center, 6 Lavrentiev Avenue, Novosibirsk, 630090, Russia

    Victor Malyshkin

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© 1999 Springer-Verlag Berlin Heidelberg

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Pudov, S. (1999). Comparative Analysis of Learning Methods of Cellular-Neural Associative Memory. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1999. Lecture Notes in Computer Science, vol 1662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48387-X_12

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  • DOI: https://doi.org/10.1007/3-540-48387-X_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66363-8

  • Online ISBN: 978-3-540-48387-8

  • eBook Packages: Springer Book Archive

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