文献类型：期刊文献

英文题名：A self-learning fuzzy modeling approach with its application to EEG time-series prediction problem

作者：Zhang, Jianhua[1]; Wang, Xingyu[1]

机构：[1] Department of Automation, School of Information Sciences and Engineering, East China University of Science and Technology, Shanghai 200237, China

年份：2008

起止页码：218

外文期刊名：Proceedings of the 27th Chinese Control Conference, CCC

收录：EI(收录号：20084011615897)

语种：英文

外文关键词：Fuzzy inference - Learning algorithms - Bandpass filters - Fuzzy filters - Membership functions - Time series

摘要：A self-learning fuzzy modeling approach based on TSK model is proposed in this paper. Based on the input-output training data, the fuzzy system optimizes the linear parameters in the THEN part of the fuzzy rules using the steady-state Kalman filter and the membership function parameters in the IF part by using supervised Gaussian learning rule. The application to EEG time-series prediction has demonstrated the practical effectiveness of the approach proposed.