Synchronization of Chaotic Neural Networks with Stochastic Perturbation and Parameter Uncertainty
Huizhong Yang · Jisuanji fangzhen · 2009
Based on drive-response synchronization principle, the synchronization control for a class of chaotic neural networks with stochastic perturbation and parameter uncertainty was investigated.By using stochastic differential equation theory, Lyapunov stability theory and LMI approach, some sufficient conditions were obtained to guarantee the global synchronization of two chaotic neural networks and a procedure to construct a synchronization controller was proposed.The derived conditions were expressed in terms of linear matrix inequalities(LMIs) and were easy to verify via the LMI toolbox.The controller thus designed is simple and easy to implement.Finally, an example shows the effectiveness of the obtained results.