Global exponential synchronization of a class of chaotic neural networks with time-varying delays

Abstract

This paper aims to present a synchronization scheme for a class of chaotic neural networks with time-varying delays, which covers the Hopfield neural networks and cellular neural networks. Using the drive-response concept, a control law of two identical chaotic neural networks is derived to achieve the exponential synchronization. Furthermore, based on the idea of vector Lyapunov function, and M-matrix theory, the sufficient conditions for global exponential synchronization of a class of chaotic neural networks are obtained. The synchronization condition is easy to verify and removed some restriction on the chaotic neural networks. Finally, some chaotic neural networks with time-varying delays are given as examples for illustration. © Springer-Verlag Berlin Heidelberg 2007.