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

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2 Author(s)
Zhang Jianhua ; Department of Automation, School of Information Sciences and Engineering, East China University of Science and Technology, Shanghai 200237, China ; Wang Xingyu

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.

Published in:

2008 27th Chinese Control Conference

Date of Conference:

16-18 July 2008