### 摘要

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.

原文 | 英語 |
---|---|

頁（從 - 到） | 2008-2014 |

頁數 | 7 |

期刊 | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |

卷 | 2 |

出版狀態 | 已發佈 - 1994 十二月 1 |

事件 | Proceedings of the 1994 IEEE International Conference on Systems, Man and Cybernetics. Part 1 (of 3) - San Antonio, TX, USA 持續時間: 1994 十月 2 → 1994 十月 5 |

### ASJC Scopus subject areas

- Control and Systems Engineering
- Hardware and Architecture

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## 引用此

Wang, C. H., Wang, W. Y., Lee, T. T., & Tseng, P. S. (1994). Fuzzy B-spline membership function (BMF) and its applications in fuzzy-neural control.

*Proceedings of the IEEE International Conference on Systems, Man and Cybernetics*,*2*, 2008-2014.