A novel LMI approach to global impulsive exponential synchronization of chaotic delayed neural networks

In this paper, the exponential synchronization problem of a class of chaotic delayed neural networks (DNNs) via impulsive control method is studied. Based on the theory of impulsive functional differential equations (FDEs), some new synchronization criteria expressed in the form of linear matrix inequalities (LMIs) are derived. The designed impulsive controller not only can globally exponentially stabilize the error dynamics, but also can control the exponential synchronization rate of the error dynamics. Furthermore, to estimate the stable region, a novel optimization control algorithm is developed, which can deal with the minimum problem with two nonlinear terms coexisting in LMIs effectively. Finally, simulation results demonstrate the effectiveness of the proposed method.