A multilayer RBF network and its supervised learning

被引：0
|
作者：
Chao, JH
Hoshino, A
Kitamura, T
Masuda, T
机构：
来源：
8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING | 2001年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper a general form of multilayer RBF networks is introduced. A complete supervised training rules for parameters are also presented. To achieve global convergence we apply a global optimazation algorithm called magic-brush method. This network is then generalized to a pyramid network. Simulations shown higher representation and generalization capability of the proposed networks comparing with the RBF and multilayer networks with sigmoid activation functions.
引用
收藏
页码：1366 / 1371
页数：6
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