Uniqueness and stability analysis of equilibrium with delayed cellular neural networks

The uniqueness and stability analysis of the equilibrium problem of the cellular neural networks with time delay is discussed in this paper. Firstly, the equilibrium point of uniqueness condition is proposed in form of LMIs by contradiction. The appropriate Lyapunov-Krasovskii function is established based on the delayed cellular neural networks model, then using the inequality skill, the delay dependent criteria of global asymptotic stability of cellular neural networks is proposed. The results are given in terms of linear matrix inequalities and can be easily calculated stability delay bounds by LMI tool-box. The results in this paper can easily get the delay-independent stability of results, and the results included in existing literature on delay independent stability analysis results. Finally, a numerical example illustrates the superiority.