Event-triggered impulsive control on quasi-synchronization of memristive neural networks with time-varying delays

This paper discusses the quasi-synchronization of memristive neural networks (MNNs) with time-varying delays via event-triggered impulsive and state feedback control approaches. The choice of different initial conditions may lead to the unexpected parameter mismatch in virtue of the state-dependent parameters of MNNs. Thus, the accurate synchronization error level and the exponential convergence rate are derived in view of the comparison principle of impulsive systems and the variable parameter formula. A co-design procedure that can be easily implemented is presented to make the synchronization error converge to a predetermined level. Then, no zeno-behavior is proved to exist in the controlled system with the proposed event-triggered condition. In addition, a self-triggered scheme is proposed to prevent continuous communication happening between the drive system and the response system. Finally, a numerical example is given to illustrate the availability of the proposed control scheme. (C) 2018 Elsevier Ltd. All rights reserved.