Exponential synchronization of inertial neural networks with mixed time-varying delays via periodically intermittent control

This paper is concerned with the problem on the exponential synchronization of inertial neural networks with discrete and finite distributed time-varying delays using intermittent control. Two kinds of time varying delays are considered: one is whose derivatives are strictly smaller than one and the other is without any restriction on the delay derivatives. Based on Lyapunov-Krasovskii functional method and applying inequality techniques, some new delay-dependent criteria are obtained to ensure the global exponential synchronization for the discussed networks, which are very simple to implement in practice and reduce the computational burden. Moreover, the exponential synchronization convergence rates depend on the norm, the transformation parameters, the control parameters and the width index of the control. Finally, some numerical examples are presented to demonstrate the validity of our results. (c) 2019 Elsevier B.V. All rights reserved.