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2012 Estimation of Approximating Rate for Neural Network in L w p Spaces
Jian-Jun Wang, Chan-Yun Yang, Jia Jing
J. Appl. Math. 2012: 1-8 (2012). DOI: 10.1155/2012/636078

Abstract

A class of Soblove type multivariate function is approximated by feedforward network with one hidden layer of sigmoidal units and a linear output. By adopting a set of orthogonal polynomial basis and under certain assumptions for the governing activation functions of the neural network, the upper bound on the degree of approximation can be obtained for the class of Soblove functions. The results obtained are helpful in understanding the approximation capability and topology construction of the sigmoidal neural networks.

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Jian-Jun Wang. Chan-Yun Yang. Jia Jing. "Estimation of Approximating Rate for Neural Network in L w p Spaces." J. Appl. Math. 2012 1 - 8, 2012. https://doi.org/10.1155/2012/636078

Information

Published: 2012
First available in Project Euclid: 14 December 2012

zbMATH: 1244.93155
MathSciNet: MR2927253
Digital Object Identifier: 10.1155/2012/636078

Rights: Copyright © 2012 Hindawi

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