Finite-time synchronization control of a class of memristor-based recurrent neural networks

Abstract

This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive–response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient conditions for finite-time synchronization between the master and corresponding slave memristor-based neural network with the designed controller. In comparison with the existing results, the proposed stability conditions are new, and the obtained results extend some previous works on conventional recurrent neural networks. Two numerical examples are provided to illustrate the effective of the design method.