Delay-Dependent Stability of Neural Networks with Time-Varying Delays

This paper investigates the problem of delay-dependent stability for continuous neural networks with time-varying delays. By constructing an augmented Lyapunov-Krasovskii functional and employing the integral inequality, reciprocally convex combination inequality and free-weighting matrix method, a less conservative stability criterion is established in terms of linear matrix inequalities. It is found that the obtained stability criterion has lower computational burden. Finally, two numerical examples used in the literature are given to show the effectiveness and superiority of the obtained criterion.