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| DENSENESS OF RADIAL-BASIS FUNCTIONS IN $\hbox{\tfL}^{\boldkey 2}{\boldkey (}\hbox{\tf R}^{\boldkey n}{\boldkey )}$ AND ITSAPPLICATIONS IN NEURAL NETWORKS |
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Citation： |
Chen Tianping,Chen Hong.DENSENESS OF RADIAL-BASIS FUNCTIONS IN $\hbox{\tfL}^{\boldkey 2}{\boldkey (}\hbox{\tf R}^{\boldkey n}{\boldkey )}$ AND ITSAPPLICATIONS IN NEURAL NETWORKS[J].Chinese Annals of Mathematics B,1996,17(2):219~226 |
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Net amount： 856 |
Authors： |
Chen Tianping; Chen Hong |
Foundation： |
Project supported by the National Natural Science
Foundation of China |
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| Abstract： |
The authors discuss problems of approximation to functions in
$L^2(R^n)$ and operators from $L^2(R^{n_1})$ to $L^2(R^{n_2})$ by
Radial-Basis Functions. The results obtained solve the
problem of capability of RBF neural networks, a basic problem in neural
networks. |
Keywords： |
Radial-basis function, Neural networks, Approximation, Operator,$L^2(R^N)$ norm |
Classification： |
41A20 |
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