Centre and variance selection for Gaussian radial basis function artificial neural networks

被引：0
|
作者：
Scheibel, F [1 ]
Steele, NC [1 ]
Low, R [1 ]
机构：
[1] Fachhsch Darmstadt, D-64295 Darmstadt, Germany
来源：
ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS | 1999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：
The quality of the response of a RBF neural network depends strongly on the calculation method of the centres and the variance matrices. This paper describes an algorithm which combines the calculation of the centres and variances of the Gaussian nodes to improve the response of a RBF neural network. The selection of the centres is made using a modified Version of the K-means algorithm and the variances are based on the sample variance-covariance matrices of the input values associated with the centres. Applications to classification and function approximation problems are considered.
引用
收藏
页码：141 / 147
页数：7
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