Impulsive-Interaction-Driven Synchronization in an Array of Coupled Neural Networks

Abstract

This paper deals with the problem of globally exponential synchronization and bipartite synchronization of coupled neural networks with impulsive interactions. Impulsive interaction means that a number of neural networks only communicate with each other at impulsive instants, while the array of neural networks are independent from each other at the remaining time. The advantage of the scheme is that communication cost can be largely reduced when only discrete communication is required. Moreover the communication links between nodes can be either positive or negative at impulsive instants. Using the Lyapunov method combined with some mathematical analysis and average impulsive interval, some efficient criteria are obtained to guarantee synchronization of impulsive coupled neural networks. Finally, the validity of our theoretical results is demonstrated by two numerical examples.