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

Authors:
Yuhua Li;Michael J. Pont;N. Barrie Jones
Affiliations:
Control and Instrumentation Research Section, Department of Engineering, University of Leicester, Leicester, UK;Control and Instrumentation Research Section, Department of Engineering, University of Leicester, Leicester, UK;Control and Instrumentation Research Section, Department of Engineering, University of Leicester, Leicester, UK
Venue:
Pattern Recognition Letters
Year:
2002

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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.