Global robust exponential stability of interval cellular neural networks with time-varying delays
区间时变细胞神经网络的全局鲁棒指数稳定性

The global robust exponential stability (GRES) of a class of interval cellular neural networks with time-varying delays is studied in this paper. A transformation is made on original system by the Leibniz-Newton formula, an analysis is also given to show that those two systems are equivalent. Based on the transformed model, applying Lyapunov-Krasovskii stability theorem for functional differential equations and the linear matrix inequality (LMI) approach, some delay-dependent criteria are respectively presented for the existence, uniqueness, and global robust exponential stability of the equilibrium for the interval delayed neural networks. The criteria given here are less conservative than those provided in the earlier references. Finally, numerical example is included to demonstrate the effectiveness and superiority of the proposed results.