Estimation of Approximating Rate for Neural Network inLwp Spaces
Joint Authors
Yang, Chan-Yun
Wang, Jianjun
Duan, Shukai
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-28
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Jianjun& Yang, Chan-Yun& Duan, Shukai. 2012. Estimation of Approximating Rate for Neural Network inLwp Spaces. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-1028954
Modern Language Association (MLA)
Wang, Jianjun…[et al.]. Estimation of Approximating Rate for Neural Network inLwp Spaces. Journal of Applied Mathematics No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-1028954
American Medical Association (AMA)
Wang, Jianjun& Yang, Chan-Yun& Duan, Shukai. Estimation of Approximating Rate for Neural Network inLwp Spaces. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-1028954
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1028954