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一类基于RBF神经网络的系统辨识算法设计与仿真

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摘要 介绍了系统辨识的意义、神经网络的优点和RBF神经网络。着重介绍了RBF神经网络的学习算法以及在系统辨识中的应用,并以仿真例子演示了RBF网络的初始化,训练和实际结果。仿真结果表明所设计的RBF网络具有较快的辨识速度和较好的辨识精度。
出处 《科技创新导报》 2009年第5期26-27,共2页 Science and Technology Innovation Herald
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  • 1郭桂蓉 谢维信 庄钊文 等.模糊模式识别[M].长沙:国防科技大学出版社,1993..
  • 2Nie J.. Constructing fuzzy model by self-organizing counterpropagation network. IEEE Transactions on System, Man and Cybernetics, 1995, 25(6): 963~970
  • 3Li R.P., Mukaidono M.. Fuzzy modeling and clustering neural network. Control and Cybernetics, 1996, 25(2): 225~242
  • 4Jang J., Sun C.. Neuro-fuzzy modeling and control. Proceedings of the IEEE, 1995, 83(3): 378-406
  • 5Keller J., Tahani H.. Neural network implementation of fuzzy logic. Fuzzy Sets and Systems, 1992, 45(1): 1~2
  • 6Chen Y.C., Teng C.C.. A model reference control structure using a fuzzy neural network. Fuzzy Sets and Systems, 1995, 73(1): 291~312
  • 7Wong C.C., Chen C.C.. A hybrid clustering and gradient descent approach for fuzzy modeling. IEEE Transactions on System, Man and Cybernetics-Part B, 1999, 29(6): 686~693
  • 8Wang L.X., Mendel M.. Fuzzy basis function, universal approximation, and orthogonal least-squares learning. IEEE Transactions on Neural Network, 1992, 3(5): 807~814
  • 9Castro J., Delgado M.. Fuzzy systems with defuzzification are universal approximators. IEEE Transactions on System, Man and Cybernetics, 1996, 26(1): 149~152
  • 10Kosko B.. Fuzzy systems as universal approximators. In: Proceedings of IEEE International Conference on Fuzzy System, San Diego, CA, 1992, 1153~1162

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