Novel delay-dependent stability criteria for delayed neural networks

The problem of delay-dependent asymptotic stability for neural networks with time-varying delays is investigated. The interval of the time delay is divided into two subintervals by introducing an arbitrary interior point. By choosing an augmented Lyapunov-Krasovskii functional and checking its variation in the two subintervals, respectively, two novel conditions are obtained in terms of linear matrix inequalities (LMIs), which can be easily checked by Matlab LMI Toolbox. Finally, four numerical examples are given that our results are less conservative than some existing ones.