Global impulsive exponential synchronization of stochastic perturbed chaotic delayed neural networks

In this paper, the global impulsive exponential synchronizationproblem of a class of chaotic delayed neural networks (DNNs) withstochastic perturbation is studied. Based on the Lyapunov stabilitytheory, stochastic analysis approach and an efficient impulsivedelay differential inequality, some new exponential synchronizationcriteria expressed in the form of the linear matrix inequality (LMI) arederived. The designed impulsive controller not only can globallyexponentially stabilize the error dynamics in mean square, but alsocan control the exponential synchronization rate. Furthermore, toestimate the stable region of the synchronization error dynamics, anovel optimization control algorithm is proposed, which can dealwith the minimum problem with two nonlinear terms coexisting in LMIseffectively. Simulation results finally demonstrate theeffectiveness of the proposed method.