实现标量混沌信号同步控制的神经网络方法

The Scalar Chaotic Signal Synchronization Control Based on Neural Networks

本文给出了一种利用线性输出神经网络实现标量混沌信号同步控制的方法。该方法利用线性输出神经网络构造被控混沌系统的模型,并基于Lyapunov理论与非线性系统控制方法,设计出神经网络权值变化规律与非线性反馈控制器,使神经网络模型的标量输出能大范围同步于给定的标量混沌信号。理论分析与计算机模拟结果都证实了这种方法的有效性。

An approach to the control and synchronization of the scalar chaotic signal by means of neural networks with linear outputs is presented. Chaotic systems controlled by neural networks with linear outputs are modeled. Based on Lyapunov theory and the control methodology of nonlinear systems, the rule of changing the weights of neural networks is figured out and a nonlinear feedback controller are designed. The scalar output of the model can be used to synchronize the given scalar chaotic signal. Both theoretical and computer simulation results illustrate the validity of the proposed method.