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A modified spreading algorithm for autoassociation in weightless neural networks

  • Christopher Browne
  • Joel de L. Pereira CastroJr
  • Amos Storkey
Poster Presentations 1 Theory III: Genaralization
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)

Abstract

This paper describes a problem with the conventional Hamming metric spreading algorithm often employed in weightless neural networks. The algorithm can cause incorrect classifications in some cases where a section of the neuron input vector is noise. The conditions under which such error occurs are described and a modified spreading algorithm proposed to overcome this problem has its validity demonstrated theoretically and tested in two practical applications.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Christopher Browne
    • 1
  • Joel de L. Pereira CastroJr
    • 1
  • Amos Storkey
    • 1
  1. 1.Imperial College of Science Technology and MedicineLondonUK

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