NONLINEAR TIME-SERIES MODELING AND PREDICTION USING GAUSSIAN RBF NETWORKS

被引：74

作者：

CHEN, S

机构：

[1] Department of Electrical and Electronics Engineering, University of Portsmouth, Portsmouth PO 3DJ, Anglesea Building

来源：

ELECTRONICS LETTERS | 1995年 / 31卷 / 02期

关键词：

NEUTRAL NETWORKS; TIME SERIES;

D O I：

10.1049/el:19950085

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

An improved clustering and recursive least squares (RLS) learning algorithm for Gaussian radial basis function (RBF) networks is described for modelling and predicting nonlinear time series. Significant performance gain can be achieved with a much smaller network compared with the usual clustering and RLS method.

引用

页码：117 / 118

页数：2

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