| 引用本文: | 章 云 ， 毛宗源， 周其节 ， 徐建闽 ，杨宜民.一种推广的模糊神经网络及学习算法[J].控制理论与应用,1998,15(1):148~151.[点击复制] |
| ZHANG Yun, MAO Zongyuan, ZHOU Qijie and XU Jianmin.A Generalized Fuzzy Neural Network and Its Learning Algorithm ZHANG Yun, MAO Zongyuan, ZHOU Qijie and XU Jianmin[J].Control Theory and Technology,1998,15(1):148~151.[点击复制] |
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| 一种推广的模糊神经网络及学习算法 |
| A Generalized Fuzzy Neural Network and Its Learning Algorithm ZHANG Yun, MAO Zongyuan, ZHOU Qijie and XU Jianmin |
| 摘要点击 1076 全文点击 443 投稿时间：1996-07-29 修订日期：1997-11-17 |
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| DOI编号 |
| 1998,15(1):148-151 |
| 中文关键词 模糊系统 神经网络 系统辨识 局部模型 |
| 英文关键词 fuzzy system neural network identification local model |
| 基金项目 |
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| 中文摘要 |
| 本文采用广义模糊神经网络实现分段建模的思想. 给出了一种广义k-均值聚类算法. 该算法能同时确定模糊规则的个数和相应的参数. 仿真结果表明该算法是可行和有效的. |
| 英文摘要 |
| This paper presents a generalized fuzzy neural network that can realize the strategy about ap- proximating a function using piecewise models. A generalized k- means algorithm is given. The number and pa- rameters of fuzzy rules can be simultaneously obtained by the algorithm. Computer simulations show that the method is feasible and efficient. |