Improved delay-dependent passivity conditions of delayed neural networks

The passivity conditions for delayed neural networks (DNNs?) are considered in this paper. 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, two numerical examples are given that our results are less conservative than some existing ones.