On-line adaptive RBF network in stationary and nonstationary envoronment

被引:0
|
作者
Todorovic, B [1 ]
Stankovic, M [1 ]
Todorovic-Zarkula, S [1 ]
机构
[1] Fac Occupat Safety, Nish, Yugoslavia
关键词
RBF; construction; prunning; nonstationary;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sequential adaptation of RBF network parameters and structure is achieved using extended Kalman Biter, Criterion for network growing is obtained from Kalman Biter's consistency test. The Optimal Brain Surgeon and Optimal Brain Damage prunning methods are derived for networks which parameters are estimated by EKF. Criteria for neurons/connections pruning are based on the statistical parameter significance test.
引用
收藏
页码:453 / 456
页数:4
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