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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/83526
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dc.contributor.authorLiu, B.-
dc.contributor.authorShi, P.-
dc.date.issued2009-
dc.identifier.citationPhysics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics, 2009; 373(21):1830-1838-
dc.identifier.issn0375-9601-
dc.identifier.issn1873-2429-
dc.identifier.urihttp://hdl.handle.net/2440/83526-
dc.description.abstractThis Letter considers the problem of delay-range-dependent stability for fuzzy bi-directional associative memory (BAM) neural networks with time-varying interval delays. Based on Lyapunov-Krasovskii theory, the delay-range-dependent stability criteria are derived in terms of linear matrix inequalities (LMIs). By constructing new Lyapunov-Krasovskii functional, stability conditions are dependent on the upper and lower bounds of the delays, which is made possible by using some advanced techniques for achieving delay dependence. A numerical example is given to illustrate the effectiveness of the proposed method. © 2009 Elsevier B.V. All rights reserved.-
dc.description.statementofresponsibilityBin Liu, Peng Shi-
dc.language.isoen-
dc.publisherElsevier Science BV-
dc.rights© 2009 Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.physleta.2009.03.044-
dc.subjectBAM neural networks-
dc.subjectFuzzy systems-
dc.subjectInterval delays-
dc.subjectLMIs-
dc.subjectStability analysis-
dc.titleDelay-range-dependent stability for fuzzy BAM neural networks with time-varying delays-
dc.typeJournal article-
dc.identifier.doi10.1016/j.physleta.2009.03.044-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest
Electrical and Electronic Engineering publications

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