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Statistical Mechanics of Neural Networks pp 461–466Cite as

Higher order memories in optimally structured neural networks

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Part of the book series: Lecture Notes in Physics ((LNP,volume 368))

Abstract

Based on one-step Hebbian learning we incorporate higher order correlations into the flexible architecture of a neural network optimized in first order. Sparse connectivity as well as a suitable summation technique eliminate the proliferation problem of higher order terms.

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Author information

Authors and Affiliations

  1. HLRZ c/o KFA Jülich, D-5170, Jülich, Germany

    Karl E. Kürten

  2. Institut für Theoretische Physik, Universität zu Köln, D-5000, Köln, Germany

    Karl E. Kürten

Authors
  1. Karl E. Kürten
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Editor information

Luis Garrido

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© 1990 Springer-Verlag

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Kürten, K.E. (1990). Higher order memories in optimally structured neural networks. In: Garrido, L. (eds) Statistical Mechanics of Neural Networks. Lecture Notes in Physics, vol 368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3540532676_69

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  • DOI: https://doi.org/10.1007/3540532676_69

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53267-5

  • Online ISBN: 978-3-540-46808-0

  • eBook Packages: Springer Book Archive

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