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Learning Vector Quantisation and the Self Organising Map

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Theory and Applications of Neural Networks

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

Abstract

A multitude of detailed circuits for artificial neural networks has been suggested. The general modes of their operation, however, are still based on much fewer underlying philosophies.

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Authors
  1. Teuvo Kohonen
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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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Kohonen, T. (1992). Learning Vector Quantisation and the Self Organising Map. 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_15

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  • DOI: https://doi.org/10.1007/978-1-4471-1833-6_15

  • 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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