| 基于改进的RBF神经网络在线辨识算法及其应用 |
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| 引用本文： | 姬晓飞,申东日,陈义俊.基于改进的RBF神经网络在线辨识算法及其应用[J].计算机仿真,2003,20(11):61-63. |
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| 作者姓名： | 姬晓飞 申东日 陈义俊 |
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| 作者单位： | 辽宁石油化工大学信息工程学院,辽宁,抚顺,113001 |
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| 摘 要： | 针对径向基函数(RBF)神经网络用于非线性系统辨识时存在的问题，对径向基函数网络的拓扑结构作了改进，并给出了改进的径向基函数(MRBF)神经网络的中心选取方法和权值在线调整算法，最后用改进的径向基函数网络对一个典型工业对象(CSTR)进行了应用研究，结果表明方法有效。
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| 关 键 词： | 系统辨识 在线辨识算法 RBF神经网络 径向基函数 非线性系统 |
| 文章编号： | 1006-9348(2003)11-0061-03 |
An on-line Identification Algorithm Based on Modified RBF Neural Networks and Its Application |
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| JI Xiao-fei,SHEN Dong-ri,CHEN Yi-jun.An on-line Identification Algorithm Based on Modified RBF Neural Networks and Its Application[J].Computer Simulation,2003,20(11):61-63. |
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| Authors: | JI Xiao-fei SHEN Dong-ri CHEN Yi-jun |
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| Abstract: | For solving some problems in nonlinear system modeling based on radial basis function neural networks, a modified construction of RBF networks is proposed. And the selection of the modified RBF networks centers and the weight tuning algorithms is proposed. The application results show that the MRBF networks successfully model a classical chemical plants. |
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| Keywords: | Neural networks On-line identification Competitive learning |
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