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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Official URL: http://dx.doi.org/10.1016/S0167-8655(01)00133-7
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 |
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Schools: | Schools > School of Computing, Science and Engineering |
Journal or Publication Title: | Pattern Recognition Letters |
Publisher: | Elsevier |
Refereed: | Yes |
ISSN: | 0167-8655 |
Related URLs: | |
Funders: | Non funded research |
Depositing User: | Yuhua Li |
Date Deposited: | 28 Jul 2015 11:23 |
Last Modified: | 15 Feb 2022 15:46 |
URI: | http://usir.salford.ac.uk/id/eprint/33138 |
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