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Desaturating coefficient for projection learning rule

  • Dmitry O. Gorodnichy
Poster Presentations 1 Theory I: Associative Memory
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)

Abstract

A Hopfield-like neural network designed with projection learning rule is considered. The relationship between the weight values and the number of prototypes is obtained. A coefficient of self-connection reduction, termed the desaturating coefficient, is introduced and the technique which allows the network to exhibit complete error correction for learning ratios up to 75% is suggested. The paper presents experimental data and provides theoretical background explaining the results.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Dmitry O. Gorodnichy
    • 1
  1. 1.Dept. of Computing ScienceUniversity of AlbertaEdmontonCanada

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