Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/4925
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dc.contributor.authorSong, Q-
dc.contributor.authorWang, Z-
dc.date.accessioned2011-04-01T14:35:07Z-
dc.date.available2011-04-01T14:35:07Z-
dc.date.issued2008-
dc.identifier.citationPhysica A: Statistical Mechanics and its Applications, 387(13): 3314-3326, May 2008en_US
dc.identifier.issn0378-4371-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/4925-
dc.descriptionThis is the post print version of the article. The official published version can be obtained from the link - Copyright 2008 Elsevier Ltden_US
dc.description.abstractIn this paper, the problem of stability analysis for a class of impulsive stochastic Cohen–Grossberg neural networks with mixed delays is considered. The mixed time delays comprise both the time-varying and infinite distributed delays. By employing a combination of the M-matrix theory and stochastic analysis technique, a sufficient condition is obtained to ensure the existence, uniqueness, and exponential p-stability of the equilibrium point for the addressed impulsive stochastic Cohen–Grossberg neural network with mixed delays. The proposed method, which does not make use of the Lyapunov functional, is shown to be simple yet effective for analyzing the stability of impulsive or stochastic neural networks with variable and/or distributed delays. We then extend our main results to the case where the parameters contain interval uncertainties. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. An example is given to show the effectiveness of the obtained results.en_US
dc.description.sponsorshipThis work was supported by the Natural Science Foundation of CQ CSTC under grant 2007BB0430, the Scientific Research Fund of Chongqing Municipal Education Commission under Grant KJ070401, an International Joint Project sponsored by the Royal Society of the UK and the National Natural Science Foundation of China, and the Alexander von Humboldt Foundation of Germany.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCohen–Grossberg neural networksen_US
dc.subjectStochastic neural networksen_US
dc.subjectExponential p-stabilityen_US
dc.subjectTime-varying delaysen_US
dc.subjectDistributed delaysen_US
dc.subjectImpulsive effecten_US
dc.titleStability analysis of impulsive stochastic Cohen–Grossberg neural networks with mixed time delaysen_US
dc.typeResearch Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.physa.2008.01.079-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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