APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

查看全文 作　　者：Li [1,2,3]Weibin;Liu [2,3]Fang;Jiao [2,3]Licheng;Zhang [1]Shuling;Li [1]Zongling

机构地区：[1]Institute of Graphics and Image Processing, Xianyang Normal University, Xianyang 712000, China;[2]National Key Laboratory for Radar Signal Processing, Xidian University, Xi'an 710071, China;[3]Insititute of Intelligent Information Processing, Xidian University, Xi'an 710071, China

出　　处：《Journal of Electronics(China)》索引2006年第23卷第1期,共4页

基　　金：Partly supported by the National Natura Science Foundation of China(No.60133010)the Natura Science Foundation of Education Department of Shaanxi Province(No.05JK312)the Natura Science Foundation of Xianyang Normal University(No.04XSYK101) 摘　　要：The functional network was introduced by E.Catillo, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance. 关键词：泛函网络神经网络神经元逼近值时频系统

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APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

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