标题:Complex-valued function approximation using an improved BP learning algorithm for wavelet neural networks
作者:Li, Sufang ;Jiang, Mingyan
作者机构:[Li, Sufang ;Jiang, Mingyan ] School of Information Science and Engineering, Shandong University, Jinan , China
通讯作者:Jiang, Mingyan
来源:Journal of Computational Information Systems
出版年:2014
卷:10
期:18
页码:7985-7992
DOI:10.12733/jcis11635
关键词:Complex-valued wavelet neural network (CVWNN); Function approximation; Momentum
摘要:A new complex-valued wavelet neural network is proposed in this paper by introducing an additive momentum and new error function for the complex-valued wavelet neural network, in which the defect of gradient descent of traditional complex-valued back propagation algorithm can be avoided. It is used for the complex-valued function approximation to verify its feasibility and effectiveness. The simulation results show that the new network has better convergence, better stability and faster running speed than the traditional complex-valued wavelet neural network and complex-valued back propagation network. Copyright © 2014 Binary Information Press.
收录类别:EI;SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84912530374&doi=10.12733%2fjcis11635&partnerID=40&md5=f75c8f594b44adae41533ae262afa4f6
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