Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur

Li, Y, Pont, MJ and Jones, NB 2002, 'Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur' , Pattern Recognition Letters, 23 (5) , pp. 569-577.

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Abstract

This paper presents a novel technique which may be used to determine an appropriate threshold for interpreting the outputs of a trained radial basis function (RBF) classifier. Results from two experiments demonstrate that this method can be used to improve the performance of RBF classifiers in practical applications.

Item Type:	Article
Schools:	Schools > School of Computing, Science and Engineering
Journal or Publication Title:	Pattern Recognition Letters
Publisher:	Elsevier
Refereed:	Yes
ISSN:	0167-8655
Related URLs:	Publication
Funders:	Non funded research
Depositing User:	Yuhua Li
Date Deposited:	28 Jul 2015 11:23
Last Modified:	15 Feb 2022 15:46
URI:	https://usir.salford.ac.uk/id/eprint/33138

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