An improved learning algorithm for compact RBF networks

被引：0

作者：

Lai, XP ^{[1
]}

Li, B ^{[1
]}

机构：

[1] Shandong Univ Weihai, Sch Informat Engn, Weihai 264209, Peoples R China

来源：

PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3 | 2005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：

An improved learning algorithm for RBF networks is presented in this paper. It allocates new neurons by a four-part novelty criterion, removes redundant neurons according to their error reduction rates, and updates output-layer weights by a recursive least-squares algorithm with Givens QR decomposition. Simulations on two benchmark problems demonstrate that the algorithm produces more compact networks than existing algorithms.

引用

页码：591 / 594

页数：4

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