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On simultaneous approximations by radial basis function neural networks

✍ Scribed by Xin Li


Book ID
108396066
Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
591 KB
Volume
95
Category
Article
ISSN
0096-3003

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This paper proposes a radial basis function neural network (RBFNN), called the q-Gaussian RBFNN, that reproduces different radial basis functions (RBFs) by means of a real parameter q. The architecture, weights and node topology are learnt through a hybrid algorithm (HA). In order to test the overal