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Novel Robust Stability Criteria for Stochastic Hopfield Neural Networks With Time Delays

Yang, Rongni and Gao, Huijun and Shi, Peng (2009) Novel Robust Stability Criteria for Stochastic Hopfield Neural Networks With Time Delays. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, 39 (2). pp. 467-474. ISSN 1083-4419

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Abstract

In this paper, the problem of asymptotic stability for stochastic Hopfield neural networks (HNNs) with time delays is investigated. New delay-dependent stability criteria are presented by constructing a novel Lyapunov-Krasovskii functional. Moreover, the results are further extended to the delayed stochastic HNNs with parameter uncertainties. The main idea is based on the delay partitioning technique, which differs greatly from most existing results and reduces conservatism. Numerical examples are provided to illustrate the effectiveness and less conservativeness of the developed techniques.

Item Type: Article
Uncontrolled Keywords: ResPubID17499, Hopfield neural networks(HNNs), Lyapunov– Krasovskii functional, robust stability, stochastic systems, time delay, uncertainties
Subjects: SEO Classification > 970109 Expanding Knowledge in Engineering
Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
FOR Classification > 0199 Other Mathematical Sciences Information Systems
Depositing User: VUIR
Date Deposited: 23 Apr 2012 04:06
Last Modified: 23 Dec 2014 04:50
URI: http://vuir.vu.edu.au/id/eprint/4714
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Citations in Scopus: 104 - View on Scopus

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