A Fast Fuzzy Neural Modelling Method for Nonlinear Dynamic Systems

Authors:
Barbara Pizzileo;Kang Li;George W. Irwin
Affiliations:
School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast BT9 5AH, UK;School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast BT9 5AH, UK;School of Electronics, Electrical Engineering & Computer Science, Queen's University Belfast, Belfast BT9 5AH, UK
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

The identification of nonlinear dynamic systems using fuzzy neural networks is studied. A fast recursive algorithm (FRA) is proposed to select both the fuzzy regressor terms and associated parameters. In comparison with the popular orthogonal least squares (OLS) method, FRA can achieve the fuzzy neural modelling with high accuracy and less computational effort.