Novel delay-dependent stability criteria of neural networks with time-varying delay

In this paper, the delay-dependent stability is investigated for neural networks with a time-varying delay. By using the augmented Lyapunov functional method and by resorting to the novel method for estimating the upper bound of the derivative of augmented Lyapunov functionals, the less conservative asymptotic stability criteria are derived in terms of linear matrix inequalities (LMIs). Two numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method.