Synchronization of coupled switched neural networks subject to hybrid stochastic disturbances - Long, Han; Ci, Jingxuan; Guo, Zhenyuan; Wen, Shiping; Huang, Tingwen (Neural networks, 2023)
In this paper, the theoretical analysis on exponential synchronization of a class of coupled switched neural networks suffering from stochastic disturbances and impulses is presented. A control law is developed and two sets of sufficient conditions are derived for the synchronization of coupled switched neural networks. First, for desynchronizing stochastic impulses, the synchronization of coupled switched neural networks is analyzed by Lyapunov function method, the comparison principle and a impulsive delay differential inequality. Then, for general stochastic impulses, by partitioning impulse interval and using the convex combination technique, a set of sufficient condition on the basis of linear matrix inequalities (LMIs) is derived for the synchronization of coupled switched neural networks. Eventually, two numerical examples and a practical application are elaborated to illustrate the effectiveness of the theoretical results. •Propose a switched coupled neural network which subject to stochastic disturbances and impulses.•Analyze the synchronization of switched neural network with desynchronizing stochastic impulses.•Analyze the synchronization of switched neural network with general stochastic impulses.