非线性系统的回归网络辨识(英文)

Identification of Nonlinear Systems Using Recurrent Neural Networks

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 .

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.