Enhanced cubic function negative-determination Lemma on stability analysis for delayed neural networks via new analytical techniques

This brief studies the stability issue of neural networks with respect to time -varying delay. First, an enhanced cubic functions negative -definiteness determination Lemma is proposed by using partitioning technique and Taylor's formula. Compared with the previous results, this Lemma can eliminate the conservatism of constraint conditions by interval -decomposition method. Second, for the sake of the relaxed positive -definiteness determination, an asymmetric Lyapunov-Krasovskii functional is presented. Third, a resulting time -varying delay -dependent stability criterion is derived by making use of some inequality techniques. Finally, the advantage of the new approach are verified theoretically and numerically.