Global exponential stability analysis of delayed cellular neural networks

Abstract

This paper presents new sufficient conditions for the global exponential stability of the equilibrium point for delayed cellular neural networks (DCNN). It is shown that the use of a more general type of Lyapunov-Krasovskii functional enables us to derive new results for exponential stability of the equilibrium point for DCNN. The results are also compared with the most recent results derived in the literature.