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New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks

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journal contribution
posted on 2017-12-06, 00:00 authored by Xian-Ming Zhang, Qing-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.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Volume

20

Issue

3

Start Page

533

End Page

539

Number of Pages

7

ISSN

1045-9227

Location

Piscataway, NJ

Publisher

Institute of Electrical and Electronics Engineers Inc.

Language

en-aus

Peer Reviewed

  • Yes

Open Access

  • No

External Author Affiliations

Centre for Intelligent and Networked Systems (CINS); Institute for Resource Industries and Sustainability (IRIS);

Era Eligible

  • Yes

Journal

IEEE transactions on neural networks.