title: New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks.
abstract: This brief deals with the problem of global asymptotic stability for a class of delayed neural networks. Some new Lyapunov-Krasovskii functionals are constructed by nonuniformly dividing the delay interval into multiple segments, and choosing proper functionals with different weighting matrices corresponding to different segments in the Lyapunov-Krasovskii functionals. Then using these new Lyapunov-Krasovskii functionals, some new delay-dependent criteria for global asymptotic stability are derived for delayed neural networks, where both constant time delays and time-varying delays are treated. These criteria are much less conservative than some existing results, which is shown through a numerical example.
authors.affiliation: Centre for Intelligent and Networked Systems and the School of Computing Sciences, Central Queensland University, Rockhampton, Qld. 4702, Australia. x.zhang@cqu.edu.au
authors.forename: Xian-Ming
authors.initials: XM
authors.lastname: Zhang
authors.forename: Qing-Long
authors.initials: QL
authors.lastname: Han