基于Wiener模型的混沌系统辨识研究

Study of Chaos Identification Based on Wiener Model

提出一种基于Ｗｉｅｎｅｒ模型辨识混沌系统的新方法。该方法利用三层前馈神经网络来辨识Ｗｉｅｎｅｒ模型中的静态非线性环节和学习混沌系统的内在规律性。同时给出了辨识混沌系统的结构和网络权值调整的学习算法。对Ｈｅｎｏｎ 系统的仿真结果表明，该方法是有效的。

A new identification structure of chaotic system is presented based on Wiener model. Three-layer feedforward neural network is used to identify nonlinear static subsystem of Wiener model and learn intrinsic feature of chaotic system. The identification structure of chaotic system and learning algorithm of neural network are both given. The simulation of Henon system shows that the identification structure works well.