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On the Construction and Training of Reformulated Radial Basis Function Neural Networks.
- Source :
- IEEE Transactions on Neural Networks; Jul2003, Vol. 14 Issue 4, p835, 12p, 1 Black and White Photograph, 1 Diagram, 3 Charts, 2 Graphs
- Publication Year :
- 2003
-
Abstract
- Presents a systematic approach for construction reformulated radial basis function (RBF) neural networks, which was developed to facilitate their training by supervised learning algorithms based on gradient descent. Admissibility conditions for RBF; Estimation of the free parameters of RBF; Experimental results.
Details
- Language :
- English
- ISSN :
- 10459227
- Volume :
- 14
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Neural Networks
- Publication Type :
- Academic Journal
- Accession number :
- 10536722
- Full Text :
- https://doi.org/10.1109/TNN.2003.813841