Novel Robust Stability Criteria for Stochastic Hopfield Neural Networks With Time Delays
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 | 159 - View on Scopus |
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