Synchronization of delayed chaotic neural networks with stochastic disturbances via periodically intermittent control

This paper deals with the synchronization problem of delayed chaotic neural networks with stochastic disturbances using periodically intermittent control. Lyapunov stability theory and free-weighting matrix method are utilized to establish stochastic synchronization criteria for designing intermittent control law, which guarantees that the synchronization error system is exponentially stable in the mean square. Under the assumption that the control period and control width are fixed and known, the desired intermittent controller is designed in terms of linear matrix inequalities. A numerical example is illustrated to demonstrate the effectiveness of the proposed method.