title: Robust stability analysis for stochastic neural networks with time-varying delay.
abstract: This brief investigates the problem of mean square exponential stability of uncertain stochastic delayed neural networks (DNNs) with time-varying delay. A novel Lyapunov functional is introduced with the idea of the discretized Lyapunov-Krasovskii functional (LKF) method. Then, a new delay-dependent mean square exponential stability criterion is derived by applying the free-weighting matrix technique and by equivalently eliminating time-varying delay through the idea of convex combination. Numerical examples illustrate the effectiveness of the proposed method and the improvement over some existing methods.
authors.affiliation: College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi 530004, China.
authors.forename: Wu-Hua
authors.initials: WH
authors.lastname: Chen
authors.forename: Wei Xing
authors.initials: WX
authors.lastname: Zheng
mesh_terms: D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D013269:Stochastic Processes; D013997:Time Factors