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Dynamics and Memory in Random and Structured Neural Networks

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Theory and Applications of Neural Networks

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

These notes provide a selection of results on modelling collective neural phenomena from completely random networks to networks with optimized architectures. The model based on binary threshold elements operating in discrete time displays emergent fascinating dynamical behaviour; in particular we demonstrate that it undergoes dynamical phase transitions and that it provides an impressive potential for content addressable memory.

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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

Editors and Affiliations

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

    J. G. Taylor BA, BSc, MA, PhD, FInstP

  2. Department of Electrical Engineering, University of Surrey, Guildford, Surrey, GU2 5XH, UK

    C. L. T. Mannion BSc, PhD, MInstP

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© 1992 Springer-Verlag London Limited

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Kürten, K.E. (1992). Dynamics and Memory in Random and Structured Neural Networks. In: Taylor, J.G., Mannion, C.L.T. (eds) Theory and Applications of Neural Networks. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1833-6_18

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  • DOI: https://doi.org/10.1007/978-1-4471-1833-6_18

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19650-1

  • Online ISBN: 978-1-4471-1833-6

  • eBook Packages: Springer Book Archive

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