Combined Convex Technique on Delay-Distribution-Dependent Stability for Delayed Neural Networks

Together with the Lyapunov-Krasovskii functional approach and an improved delay-partitioning idea, one novel sufficient condition is derived to guarantee a class of delayed neural networks to be asymptotically stable in the mean-square sense, in which the probabilistic variable delay and both of delay variation limits can be measured. Through combining the reciprocal convex technique and convex technique one, the criterion is presented via LMIs and its solvability heavily depends on the sizes of both time-delay range and its variations, which can become much less conservative than those present ones by thinning the delay intervals. Finally, it can be demonstrated by four numerical examples that our idea reduces the conservatism more effectively than some earlier reported ones

Combined Convex Technique on Delay-Distribution-Dependent Stability for Delayed Neural Networks

Together with the Lyapunov-Krasovskii functional approach and an improved delay-partitioning idea, one novel sufficient condition is derived to guarantee a class of delayed neural networks to be asymptotically stable in the mean-square sense, in which the probabilistic variable delay and both of delay variation limits can be measured. Through combining the reciprocal convex technique and convex technique one, the criterion is presented via LMIs and its solvability heavily depends on the sizes of both time-delay range and its variations, which can become much less conservative than those present ones by thinning the delay intervals. Finally, it can be demonstrated by four numerical examples that our idea reduces the conservatism more effectively than some earlier reported ones

Novel stability of cellular neural networks with interval time-varying delay

In this paper, the asymptotic stability is investigated for a class of cellular neural networks with interval time-varying delay (that is, 0 < h1 < d (t) < h2). By introducing a novel Lyapunov functional with the idea of partitioning the lower bound h1 of the time-varying delay, a new criterion of asymptotic stability is derived in terms of a linear matrix inequality (LMI), which can be efficiently solved via standard numerical software. The criterion proves to be less conservative than most of the existing results, and the conservatism could be notably reduced by thinning the delay partitioning. Two examples are provided to demonstrate the less conservatism and effectiveness of the proposed stability conditions