Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/85022
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dc.contributor.authorZhang, Y.-
dc.contributor.authorShi, P.-
dc.contributor.authorNguang, S.-
dc.contributor.authorZhang, J.-
dc.contributor.authorKarimi, H.-
dc.date.issued2014-
dc.identifier.citationNeurocomputing, 2014; 140:1-7-
dc.identifier.issn0925-2312-
dc.identifier.issn1872-8286-
dc.identifier.urihttp://hdl.handle.net/2440/85022-
dc.description.abstractThis paper is concerned with stochastic finite-time boundedness analysis for a class of uncertain discrete-time neural networks with Markovian jump parameters and time-delays. The concepts of stochastic finite-time stability and stochastic finite-time boundedness are first given for neural networks. Then, applying the Lyapunov approach and the linear matrix inequality technique, sufficient criteria on stochastic finite-time boundedness are provided for the class of nominal or uncertain discrete-time neural networks with Markovian jump parameters and time-delays. It is shown that the derived conditions are characterized in terms of the solution to these linear matrix inequalities. Finally, numerical examples are included to illustrate the validity of the presented results. © 2014 Elsevier B.V.-
dc.description.statementofresponsibilityYingqi Zhang, Peng Shi, Sing Kiong Nguang, Jianhua Zhang, Hamid Reza Karimi-
dc.language.isoen-
dc.publisherElsevier Science-
dc.rights© 2014 Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.neucom.2013.12.054-
dc.subjectMarkovian jump systems; neural networks; discrete-time systems; stochastic finite-time boundedness; linear matrix inequalities-
dc.titleFinite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps-
dc.typeJournal article-
dc.identifier.doi10.1016/j.neucom.2013.12.054-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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