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Proceedings Paper

Implementation of a Variable Cluster Self Organising Algorithm for High Speed Unsupervised Pattern Classification (Lost in {0, 1}N space)
Author(s): Martin Johnson; Nigel Allinson
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Paper Abstract

Traditional neural networks for pattern classification use linear decisions to partition a multivalued high dimensional pattern space. This paper shows that the properties of binary space ({0, 1}N space) make it well suited for these tasks and a simple training algorithm is given. A simple measure of network ordering is used to allow a variable number of clusters and continuous learning.

Paper Details

Date Published: 1 February 1990
PDF: 8 pages
Proc. SPIE 1197, Automated Inspection and High-Speed Vision Architectures III, (1 February 1990); doi: 10.1117/12.969939
Show Author Affiliations
Martin Johnson, York University (United Kingdom)
Nigel Allinson, York University (United Kingdom)


Published in SPIE Proceedings Vol. 1197:
Automated Inspection and High-Speed Vision Architectures III
Michael J. W. Chen, Editor(s)

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