引用本文:任雪梅.非线性系统的回归网络辨识(英文)[J].控制理论与应用,2001,18(6):944~948.[点击复制]
REN Xue-mei.Identification of Nonlinear Systems Using Recurrent Neural Networks[J].Control Theory and Technology,2001,18(6):944~948.[点击复制]
非线性系统的回归网络辨识(英文)
Identification of Nonlinear Systems Using Recurrent Neural Networks
摘要点击 2023  全文点击 1120  投稿时间:2000-02-24  修订日期:2000-11-08
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DOI编号  10.7641/j.issn.1000-8152.2001.6.029
  2001,18(6):944-948
中文关键词  回归网络  动态反向传播算法  系统辨识
英文关键词  recurrent neural network  dynamic backpropagation algorithm  system identification
基金项目  
作者单位
任雪梅 北京理工大学 自动控制系, 北京 100081 
中文摘要
      针对未知非线性系统的辨识问题, 本文提出了一种新型的回归网络模型. 证明了该网络模型在一定条件下能够逼近非线性系统的输入输出关系, 提出了用于训练网络前向连接和反向连接权值的动态反向传播算法. 仿真结果验证该方法的有效性.
英文摘要
      This paper proposes a new type of recurrent neural network for the identification of a class of unknown nonlinear system. It is proved that the proposed network with appropriate conditions can represent unknown input_output relationship of nonlinear systems. The dynamic backpropagation algorithm is employed to estimate the weights of both the feedforward and feedback connections in the networks. The proposed schemes have been successfully applied to modeling nonlinear plants.