| 模糊小脑模型神经网络 |
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| 引用本文： | 周旭东,王国栋.模糊小脑模型神经网络[J].自动化学报,1998,24(2):173-178. |
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| 作者姓名： | 周旭东 王国栋 |
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| 作者单位： | 1.东北大学轧制技术及连轧自动化国家重点实验室,沈阳 |
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| 摘 要： | 提出输入层具有一定隶属度的模糊小脑模型神经网络(Fuzzy CMAC),它比小脑
模型CMAC(Cerebellar Model Articulation Controller)能更真实地描述客观世界.给出n维
Fuzzy CMAC算法,仿真结果表明Fuzzy CMAC比小脑模型CMAC具有如下优点:学习收敛
速度快得多,可以学习模糊规则.Fuzzy CMAC比CMAC优越,使CMAC成为Fuzzy CMAC
的特例.
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| 关 键 词： | 模糊小脑模型 模糊小脑模型算法 小脑模型 小脑模型算法 |
| 收稿时间： | 1995-12-18 |
Fuzzy CMAC Neural Network |
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| Zhou Xudong,Wang Guodong.Fuzzy CMAC Neural Network[J].Acta Automatica Sinica,1998,24(2):173-178. |
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| Authors: | Zhou Xudong Wang Guodong |
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| Affiliation: | 1.Rolling Tech.&Tandem Automation state Key Laboratory.Northeastern University,Shenyang |
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| Abstract: | A Fuzzy Cerebellar Model Articulation Controller (FCMAC) is proposed in this
paper. A fuzzy membership function μ(k) is introduced into the FCMAC's input layer. The
FCMAC can describe thd world more really than the CMAC can. The FCMAC algorithms for
n dimensional problem are given. Simulation results show that the FCMAC has a faster convergence
speed than CMAC. The FCMAC can also learn fuzzy reasoning rules (for fuzzy control).
In a word, the FCMAC is a better neural network than CMAC, and it makes CMAC as
the special case of FCMAC. |
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| Keywords: | ,Cold standby system,redundant structure,reliability estimation, |
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