Trajectory Tracking of Complex Dynamical Network for Delayed Recurrent Neural Network via Control V-Stability

Abstract

In this paper the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a dynamical network with each node being a Chen’s dynamical system.