New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks
journal contributionposted on 2017-12-06, 00:00 authored by Xian-Ming ZhangXian-Ming Zhang, Qing-Long HanQing-Long Han
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.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Number of Pages7
PublisherInstitute of Electrical and Electronics Engineers Inc.
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External Author AffiliationsCentre for Intelligent and Networked Systems (CINS); Institute for Resource Industries and Sustainability (IRIS);