Generating Chaos by Using Dynamic Neural Networks
Chunxia Fan · Journal of Yancheng Institute of Technology · 2005
Propose a new approach to generate chaos via dynamic neural networks according to inverse optimal control for nonlinear systems. The controller is derived to force dynamic neural network to reproduce intended chaos. In light of the nature of chaotification, a track control is subtly introduced. This method need not estimate the Lapunov exponent of the chaotic attractor so that computation is reduced greatly, which means this scheme is simple in practical application. Lorenz system and Rossler chaos are used for examples. The numerical simulation results demonstrate the effectiveness and excellent performance of the suggested controller.