A modified spreading algorithm for autoassociation in weightless neural networks

Christopher Browne, Joel de L. Pereira Castro Jr., Amos Storkey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationArtificial Neural Networks — ICANN 96
Subtitle of host publication1996 International Conference Bochum, Germany, July 16–19, 1996 Proceedings
EditorsChristoph von der Malsburg, Werner von Seelen, Jan C. Vorbrüggen, Bernhard Sendhoff
PublisherSpringer
Pages569-574
Number of pages6
ISBN (Electronic)978-3-540-68684-2
ISBN (Print)978-3-540-61510-1
DOIs
Publication statusPublished - 1996

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume1112
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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