| T-S型模糊RBF神经网络的结构研究 |
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| 引用本文： | 鲍鸿,黄心汉,李锡雄.T-S型模糊RBF神经网络的结构研究[J].华中科技大学学报(自然科学版),1999,27(1):11-13. |
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| 作者姓名： | 鲍鸿 黄心汉 李锡雄 |
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| 作者单位： | 1. 广东工业大学电气工程及自动化系
2. 华中理工大学自动控制工程系 |
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| 摘 要： | 提出Ｔ－Ｓ型模糊ＲＢＦ神经网络模型结构，讨论该模型参数的输入空间模糊最优聚类学习算法．仿真结果验证了学习算法的有效性和可行性，表明Ｔ－Ｓ型模糊ＲＢＦ神经网络可逼近任意多变量非线性函数．
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| 关 键 词： | 模糊神经网络 模糊控制 RBF神经网络 模式识别 |
| 修稿时间： | 1998-09-01. |
A Study of the T-S Fuzzy RBF Neural Network |
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| Bao Hong,Huang Xinhan,Li Xixiong.A Study of the T-S Fuzzy RBF Neural Network[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,1999,27(1):11-13. |
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| Authors: | Bao Hong Huang Xinhan Li Xixiong |
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| Institution: | Bao Hong Huang Xinhan Li Xixiong |
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| Abstract: | A new type of Takagi Sugeno (T S) fuzzy radial basis function (RBF) in neural network is presented. A fuzzy optimum cluster algorithm in the input space is discussed. The simulation results show that the T S fuzzy RBF neural network approximates nonlinear function with any multi variable with any degree of accuracy, verifying the cluster algorithm being effective and available. |
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| Keywords: | fuzzy neural network fuzzy control RBF neural network model identification |
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