Event-Triggered Exponential Synchronization of Nonfragile Neural Networks

Abstract

Based on event-triggered mechanism, the exponential synchronization for a class of neural networks (NNs) with distributed and discrete delays under nonfragile controller is researched in this article. Firstly, whether the controller gain disturbance occurs or not is described by a random variable, which obeys the Bernoulli distribution. Secondly, the event-triggered mechanism is introduced into the exponential synchronization of NNs. Next, based on the characteristics of sawtooth structure, a new bilateral Lyapunov–Krasovskii functional (LKF) is constructed, which involves more system information. Through the use of improved integral inequality, some sufficient conditions are achieved for the exponential stability of the synchronization error system. Then, a nonfragile controller is designed based on the decoupling technique. Finally, two examples are used to illustrate the validity and superiority of these results.