Global finite-time stabilization of memristor-based neural networks with time-varying delays via hybrid control

摘要

In this paper, the problem of finite-time stabilization for a class of memristor-based neural networks with time-varying delays is investigated by using hybrid impulsive and nonlinear feedback controllers. Based on the theory of the differential equations with discontinuous right and Lyapunov function approach, several sufficient conditions are derived to guarantee the finite-time stabilization of memristor-based neural networks. Especially, the existing criteria are improved since the impulsive control is introduced in the convergence time. Finally, the effectiveness of the obtained results is illustrated by two numerical examples.