首页> 外文会议>IEEE Interantional Conference on Systems, Man and Cybernetics >Identification of a nonlinear dynamic systems using recurrent multilayer neural networks
【24h】

Identification of a nonlinear dynamic systems using recurrent multilayer neural networks

机译:使用反复多层神经网络识别非线性动力系统

获取原文

摘要

Multilayer neural networks have been used successfully in many system identification and control problems, and numerous applications have been suggested in the literature. Backpropagation is one of the standard methods used in these cases to adjust the weights/biases of the neural networks. In recent paper[1,2,3], the authors suggested the use of multilayer neural networks for the identification and control of non-linear dynamical systems and proposed an extension of the Back-propagation method. In this paper, system identification with recurrent multilayer neural networks is studied, and we present in detail the update-rules of the dynamic Back-propagation method, so that it can be applied in a straightforward manner for the optimisation of the parameters of these recurrent multilayer neural networks.
机译:多层神经网络已经成功使用,在许多系统识别和控制问题中,在文献中提出了许多应用。 BackPropagation是在这些情况下使用的标准方法之一,以调整神经网络的权重/偏置。在近期纸张[1,2,3]中,作者建议使用多层神经网络来识别和控制非线性动力系统,并提出了后传播方法的延伸。在本文中,研究了具有复发多层神经网络的系统识别,我们详细介绍了动态反向传播方法的更新规则,从而可以以直接的方式应用于优化这些复发的参数多层神经网络。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号