Event-Triggered Synchronization for Discrete-Time Neural Networks With Unknown Delays
Nannan Rong, Zhanshan Wang, Xiangpeng Xie, Sanbo Ding
Abstract
This brief is concerned with the event-triggered synchronization of delayed discrete-time neural networks. Under the assumption that the delay is unknown, a delay-free slave system is chosen. In this step, the delay term in master system is taken as a bounded disturbance. Whereafter, a discrete-time periodic triggering algorithm is proposed to govern the updating instants of controller. Based on this method, the sensor only calculates the triggering algorithm periodically instead of the common continuous manners. A discrete-time Witringer-based Lyapunov functional is constructed aiming at making full use of the sawtooth constraint of the sampling signals. Under such a framework, sufficient conditions are developed to ensure the boundedness of synchronization error. Finally, the effectiveness of the proposed method is illustrated by a simulation example.