An active learning approach for radial basis function neural networks
This paper presents a new Active Learning algorithm to train Radial Basis Function (RBF) Artificial Neural Networks (ANN) for model reduction problems. The new approach is based on the assumption that the unobserved training data y at input x, lies within a set F x y f x y f x ( ) : ( ) ( ) = ! ! &q...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTM Press
2006
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/4112/1/JTD_2005_29.pdf http://eprints.utm.my/id/eprint/4112/ http://www.penerbit.utm.my/onlinejournal/45/D/JTDis45D05.pdf |
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