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.

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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.

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Published

2001-06-20

Issue

Vol. 1 (2001): Environment. Technology. Resources. Proceedings of the 3rd International Scientific and Practical Conference

Section

Computer Technology

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.