A multilayer RBF network and its supervised learning

被引：0

作者：

Chao, JH ^{[1
]}

Hoshino, M ^{[1
]}

Kitamura, T ^{[1
]}

Masuda, T ^{[1
]}

机构：

[1] Chuo Univ, Dept Elect & Elect Commun Engn, Bunkyo Ku, Tokyo 1126551, Japan

来源：

IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS | 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 can be naturally extended into a pyramid topology. Simulations shown higher representation and generalization capability of the proposed networks comparing with the RBF and multilayer networks with sigmoid activation functions.

引用

页码：1995 / 2000

页数：6

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