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

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Yang, Rongni, 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

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
URI https://vuir.vu.edu.au/id/eprint/4714
Official URL http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Subjects Historical > SEO Classification > 970109 Expanding Knowledge in Engineering
Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Historical > FOR Classification > 0199 Other Mathematical Sciences Information Systems
Keywords ResPubID17499, Hopfield neural networks(HNNs), Lyapunov– Krasovskii functional, robust stability, stochastic systems, time delay, uncertainties
Citations in Scopus 158 - View on Scopus
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