L~p Approximation Capability of RBF Neural Networks
<正> Lp approximation capability of radial basis function(RBF)neural networks is investigated.Ifg:R+1→R1 and g(‖x‖Rn)∈ L(loc)p(Rn)with 1≤p<∞,then the RBF neural networks with g as theactivation function can approximate any given function in Lp(K)with any accuracy for any compacts...
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Veröffentlicht in: | Acta mathematica Sinica. English series 2008-09, Vol.24 (9), p.1533-1540 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | <正> Lp approximation capability of radial basis function(RBF)neural networks is investigated.Ifg:R+1→R1 and g(‖x‖Rn)∈ L(loc)p(Rn)with 1≤p<∞,then the RBF neural networks with g as theactivation function can approximate any given function in Lp(K)with any accuracy for any compactset K in Rn,if and only if g(x)is not an even polynomial. |
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ISSN: | 1439-8516 1439-7617 |
DOI: | 10.1007/s10114-008-6423-x |