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Improving training of radial basis function network for classification of power quality disturbances
journal contribution
posted on 2023-05-16, 13:37 authored by Hoang, TA, Nguyen, TFeatures extracted from non-stationary and transitory power quality disturbances using wavelet transform modulus maxima can serve as powerful discriminating features for wavelet-based classification of these disturbances. Using these features, a comprehensive 'knowledge-based' algorithm is proposed for the training of the radial basis function network classifier, so that at its convergence the network gives both the optimal feature weight vector as well as the cluster centres and scaling widths.
History
Publication title
Electronics LettersVolume
38Issue
17Pagination
976-977ISSN
0013-5194Department/School
School of EngineeringPublisher
The Institution of Electrical Engineers Publishing DepartmentPlace of publication
UKRepository Status
- Restricted