TY - CONF
T1 - A training method for improving the generalization performance of radial basis function networks
AU - Duan, Shaojie
AU - He, Chao
AU - Xu, Lixin
AU - Ma, Dongsheng
PY - 2000
Y1 - 2000
N2 - To improve the generalization performance of RBF networks, samples having been divided into training set and evaluating set, a novel training algorithm is proposed for adjusting the width of center point set based on the standard deviation of evaluating set error. Simulation results show this method is effective in improving the generalization performance of RBF networks. The performance of generalization of RBF network can be remarkably improved by using this training method.
AB - To improve the generalization performance of RBF networks, samples having been divided into training set and evaluating set, a novel training algorithm is proposed for adjusting the width of center point set based on the standard deviation of evaluating set error. Simulation results show this method is effective in improving the generalization performance of RBF networks. The performance of generalization of RBF network can be remarkably improved by using this training method.
KW - Generalization performance
KW - Radial basis function networks
KW - Samples classification
KW - Width of center point set
UR - http://www.scopus.com/inward/record.url?scp=0034591620&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:0034591620
SP - 859
EP - 863
T2 - Proceedings of the 3th World Congress on Intelligent Control and Automation
Y2 - 28 June 2000 through 2 July 2000
ER -