Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays.

Abstract

This paper deals with the synchronization for discrete-time coupled neural networks (DTCNNs), in which stochastic perturbations and multiple delays are simultaneously involved. The multiple delays mean that both discrete time-varying delays and distributed delays are included. Time-triggered impulsive control (TTIC) is proposed to investigate the synchronization issue of the DTCNNs based on the recently proposed impulsive control scheme for continuous neural networks with single time delays. Furthermore, a novel event-triggered impulsive control (ETIC) is designed to further reduce the communication bandwidth. By using linear matrix inequality (LMI) technique and constructing appropriate Lyapunov functions, some sufficient criteria guaranteeing the synchronization of the DTCNNs are obtained. Finally, We propose a simulation example to illustrate the validity and feasibility of the theoretical results obtained.