International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 12 - Number 1 |
Year of Publication: 2010 |
Authors: B.M.Singhal |
10.5120/1644-2211 |
B.M.Singhal . Article:A Moderate Algorithm for Generalized Radial basis Function Neural Networks. International Journal of Computer Applications. 12, 1 ( December 2010), 10-12. DOI=10.5120/1644-2211
A Radial Basis Function ( RBF ) neural network can be regarded as a feed forward network composed of multiple layers of neurons with entirely different roles. The input layer made of sensory units that connect the network to its environment. A radial basis function neural network depends mainly upon an adequate choice of the number and positions of its basis function centers. In case of generalized RBF neural network, the output layer is linear and supplying each layer response as the linear combination of the hidden responses. In this paper we have proposed a moderate algorithm for most generalized form of RBF neural network and the results may be reduced for various forms of RBF and other artificial neural networks as particular cases.