APPLICATION OF CLUSTERING METHOD IN THE RBF NEURAL NETWORKS

Authors

  • Pēteris Grabusts Rezekne Academy of Technologies (LV)

DOI:

https://doi.org/10.17770/etr2001vol1.1928

Keywords:

RBF neural network, clustering, K-means

Abstract

This paper describes one of classification algorithms, cluster analysis, that plays a significant role in the implementation of learning algorithm as applied to RBF-type artificial mural networks. The mathematical description of the K-means clustering algorithm is given and its implementation is demonstrated by experiment.

Downloads

References

Hush D.R., Horne B.G. Progress in Supervised Neural Networks. What’s new since Lippmann?, IEEE Signal Processing Magazine, January, 1993, vol.l0,No 1.

Статистические методы для ЭВМ. - Москва: Наука, 1986.

Панкова Л.А., Трахтенгерц Э.А. Субъективность в интелектуальном анализе данных. - Москва: Препринт/Институт проблем управления, 1999.

Downloads

Published

20.06.2001

How to Cite

[1]
P. Grabusts, “APPLICATION OF CLUSTERING METHOD IN THE RBF NEURAL NETWORKS”, ETR, vol. 1, pp. 257–262, Jun. 2001, doi: 10.17770/etr2001vol1.1928.