Size-reducing RBF networks
説明
An approach is proposed to reduce the complexity of radial basis function (RBF) networks. This approach starts with enough hidden nodes and reduces the number of nodes in the course of learning. The algorithm can be employed in problems where only the performance index of the network output is given, as well as in the supervised training problems where the desired output values are available. Also, it is applicable to classification problems and function approximation problems.
収録刊行物
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- IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)
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IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339) 2 1308-1312, 2003-01-22
IEEE
