Less conservative stability criteria for neural networks with interval time-varying delay based on delay-partitioning approach

This paper is concerned with the problem of delay-dependent asymptotic stability for neural networks with interval time-varying delay. A delay-partitioning approach is used in this paper, in which the delay interval is partitioned into multiple equidistant subintervals and slightly different Lyapunov-Krasovskii functional is constructed on these intervals. By combining with reciprocally convex approach, several less conservative delay-dependent stability criteria are derived in terms of linear matrix inequality. Numerical examples are given to illustrate the effectiveness and less conservatism of the proposed method.