Exponential Robust Stability of Cellular Neural Networks

Abstract

A novel method is proposed in this note for exponential stability of cellular neural networks with time-varying delay. New delay-dependent exponential stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, a numerical example is given to demonstrate the effect of the proposed method. Keywords-Delayed cellular neural networks (DCNNs), Lyapunov functional, LMI, Exponential stability In this paper we consider exponential stability problem for time-varying delay cellular neural networks. By utilizing new Lyapunov-Krasovskii functional, we propose the novel sufficient conditions for the time-varying delay neural network. The sufficient conditions obtained in this paper are looser than those in the former literature. Specially, our stability results include the time delay independent ones in the former literature. The stability conditions obtained in this paper are all in the form of LMIs. Finally, a numerical example will be given to show the effectiveness of the main results.