Stability Analysis of Delayed Neural Networks via a Time-Varying Lyapunov Functional

This article concerns the stability issues of neural networks with time-varying delays. The purpose is to establish less conservative stability conditions for delayed neural networks. In order to achieve this goal, a time-varying Lyapunov functional method is proposed for stability analysis of delayed neural networks. The main feature of this method is to construct different Lyapunov functionals in different time-varying delay subintervals, which relaxes the restriction requirement of traditional Lyapunov functionals constructing a common Lyapunov functional in the whole delay interval. Based on the developed time-varying Lyapunov functional, some new stability conditions for delayed neural networks are obtained. Finally, two examples are given to verify the effectiveness of the derived stability conditions.