| T-S型模糊RBF神经网络快速学习算法 |
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| 引用本文： | 鲍鸿,黄心汉,李锡雄.T-S型模糊RBF神经网络快速学习算法[J].华中科技大学学报(自然科学版),1999,27(2):18. |
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| 作者姓名： | 鲍鸿 黄心汉 李锡雄 |
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| 作者单位： | 华中理工大学自动控制工程系，广东工业大学电气工程及自动化系 |
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| 摘 要： | 针对Ｔ－Ｓ型模糊ＲＢＦ神经网络输入空间模糊最优聚类算法运算量大、运算速度低的缺点，提出基于输出空间模式聚类的快速学习算法，以满足多变量系统实时性要求．仿真结果表明该快速学习算法不仅可以达到要求的辨识精度，而且可有效地提高运算速度
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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 Fast Learning Algorithm of the T S Fuzzy RBF Neural Network |
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| Bao Hong,Huang Xinhan,Li Xixiong.A Study of the Fast Learning Algorithm of the T S Fuzzy RBF Neural Network[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,1999,27(2):18. |
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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: | Based on the analyses of the fuzzy optimum cluster algorithm in the input space, the authors find that a drawback of the algorithm is time consuming and computationally expensive. For the on line desire of multi variable control system, a fast learning algorithm is presented based on the model cluster in the output space. The simulation results show that the fast learning algorithm can meet any given identification accuracy and can save the operation time. |
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| Keywords: | fuzzy neural network fuzzy control RBF neural network model identification |
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