Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach

The global exponential stability for a class of uncertain delayed cellular neural networks (DCNN) with multiple time-varying delays is considered. Delay-dependent criteria are proposed to guarantee the robust stability of DCNN via linear matrix inequality (LMI) approach. Two classes of uncertainties on feedback matrices are investigated. Some numerical examples are given to illustrate the effectiveness of our results. From the numerical simulation, significant improvement over the recent results can be observed.