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

Yuhua Li, Michael J Pont

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

This paper develops a technique for determining a reliable threshold for RBF classifiers. A two-phase approach is proposed to RBF classifier use in situations where unknown faults may occur: the first phase deals with the possibility of unknown faults; in the second phase, the classifier threshold is modified through retraining using all available data, including newly collected data about unknown faults. The approach is easy to use and is demonstrated to be particularly effective in classification problems where novelty detection capability is required.
Original languageEnglish
Pages (from-to)569-577
JournalPattern Recognition Letter
Volume23
Issue number5
DOIs
Publication statusPublished (in print/issue) - Mar 2002

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