Share Email Print
cover

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
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top