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Competition between feed-forward and lateral information processing in layered neural networks

  • Formal Tools and Computational Models of Neurons and Neural Net Architectures
  • Conference paper
  • First Online:
Biological and Artificial Computation: From Neuroscience to Technology (IWANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

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Abstract

We use replica theory to analyse layered networks of binary neurons, with lateral Hebbian-type synapses within individual layers, in combination with strictly feed-forward Hebbian-type synapses between successive layers. The competition between two qualitatively different modes of operation, feed-forward versus lateral, induces interesting transitions, and allows for the identification of an optimal value for the balance between the two synapse types.

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Author information

Authors and Affiliations

  1. Department of Mathematics, King's College London Strand, WC2R 2LS, London, UK

    A. C. C. Coolen

  2. Laboratorio de Ensenada, Instituto de Fisica, UNAM, A. Postal 2681, Ensenada B.C., Mexico

    L. Viana

Authors
  1. A. C. C. Coolen
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  2. L. Viana
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Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

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© 1997 Springer-Verlag Berlin Heidelberg

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Coolen, A.C.C., Viana, L. (1997). Competition between feed-forward and lateral information processing in layered neural networks. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032483

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  • DOI: https://doi.org/10.1007/BFb0032483

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

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