Global anti-synchronization of memristor-based recurrent neural networks with time-varying delays and impulsive effects

In this paper, the anti-synchronization control of memristor-based recurrent neural networks with impulsive perturbations is studied. By using differential inclusions theory, the Lyapnov functional method and the inequality technique, some sufficient conditions are derived to ensure impulsive exponential anti-synchronization of memristor-based recurrent neural networks. The new proposed results involve the impulsive effects and improve the earlier publications. Numerical examples are given to show the effectiveness of our new schemes.