TY - JOUR

T1 - Fuzzy B-spline membership function (BMF) and its applications in fuzzy-neural control

AU - Wang, Chi Hsu

AU - Wang, Wei Yen

AU - Lee, Tsu Tian

AU - Tseng, Pao Shun

PY - 1994

Y1 - 1994

N2 - A general methodology for constructing fuzzy membership functions via B-spline curve is proposed. By using the method of least-squares, we translate the empirical data into the form of the control points of B-spline curves to construct fuzzy membership functions. This unified form of fuzzy membership functions is called as B-spline membership functions (BMF's). By using the local control property of B-spline curve, the BMF's can be tuned locally during learning process. For the control of a model car through fuzzy-neural networks, it is shown that the local tuning of BMF's can indeed reduce the number of iterations tremendously.

AB - A general methodology for constructing fuzzy membership functions via B-spline curve is proposed. By using the method of least-squares, we translate the empirical data into the form of the control points of B-spline curves to construct fuzzy membership functions. This unified form of fuzzy membership functions is called as B-spline membership functions (BMF's). By using the local control property of B-spline curve, the BMF's can be tuned locally during learning process. For the control of a model car through fuzzy-neural networks, it is shown that the local tuning of BMF's can indeed reduce the number of iterations tremendously.

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M3 - Conference article

AN - SCOPUS:0028740250

VL - 2

SP - 2008

EP - 2014

JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

SN - 0884-3627

T2 - Proceedings of the 1994 IEEE International Conference on Systems, Man and Cybernetics. Part 1 (of 3)

Y2 - 2 October 1994 through 5 October 1994

ER -