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Article: Stability and dissipativity analysis of distributed delay cellular neural networks

TitleStability and dissipativity analysis of distributed delay cellular neural networks
Authors
KeywordsCellular neural networks
Dissipativity
Distributed delay
Integral partitioning
Issue Date2011
Citation
IEEE Transactions on Neural Networks, 2011, v. 22 n. 6, p. 976-981 How to Cite?
AbstractIn this brief, the problems of delay-dependent stability analysis and strict Q,S,R α-dissipativity analysis are investigated for cellular neural networks (CNNs) with distributed delay. First, by introducing an integral partitioning technique, two new forms of LyapunovKrasovskii functionals are constructed, and improved distributed delay-dependent stability conditions are established in terms of linear matrix inequalities. Based on this criterion, a new sufficient delay and α-dependent condition is given to guarantee that the CNNs with distributed delay are strictly Q, S, R α-dissipative. The results developed in this brief can tolerate larger allowable delay than existing ones in the literature, which is demonstrated by several examples. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/139435
ISSN
2011 Impact Factor: 2.952
ISI Accession Number ID
Funding AgencyGrant Number
University of Hong Kong7137/09E
Funding Information:

Manuscript received September 7, 2010; revised December 23, 2010; accepted March 6, 2011. Date of publication May 13, 2011; date of current version June 2, 2011. This work was supported in part by the University of Hong Kong General Research Fund, under Grant 7137/09E.

References

 

DC FieldValueLanguage
dc.contributor.authorFeng, Zen_HK
dc.contributor.authorLam, Jen_HK
dc.date.accessioned2011-09-23T05:49:28Z-
dc.date.available2011-09-23T05:49:28Z-
dc.date.issued2011en_HK
dc.identifier.citationIEEE Transactions on Neural Networks, 2011, v. 22 n. 6, p. 976-981en_HK
dc.identifier.issn1045-9227en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139435-
dc.description.abstractIn this brief, the problems of delay-dependent stability analysis and strict Q,S,R α-dissipativity analysis are investigated for cellular neural networks (CNNs) with distributed delay. First, by introducing an integral partitioning technique, two new forms of LyapunovKrasovskii functionals are constructed, and improved distributed delay-dependent stability conditions are established in terms of linear matrix inequalities. Based on this criterion, a new sufficient delay and α-dependent condition is given to guarantee that the CNNs with distributed delay are strictly Q, S, R α-dissipative. The results developed in this brief can tolerate larger allowable delay than existing ones in the literature, which is demonstrated by several examples. © 2011 IEEE.en_HK
dc.languageengen_US
dc.relation.ispartofIEEE Transactions on Neural Networksen_HK
dc.rights©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectCellular neural networksen_HK
dc.subjectDissipativityen_HK
dc.subjectDistributed delayen_HK
dc.subjectIntegral partitioningen_HK
dc.titleStability and dissipativity analysis of distributed delay cellular neural networksen_HK
dc.typeArticleen_HK
dc.identifier.emailLam, J:james.lam@hku.hken_HK
dc.identifier.authorityLam, J=rp00133en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TNN.2011.2128341en_HK
dc.identifier.pmid21558058-
dc.identifier.scopuseid_2-s2.0-79957975572en_HK
dc.identifier.hkuros196479en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79957975572&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume22en_HK
dc.identifier.issue6en_HK
dc.identifier.spage976en_HK
dc.identifier.epage981en_HK
dc.identifier.isiWOS:000291355700014-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridFeng, Z=35770539900en_HK
dc.identifier.scopusauthoridLam, J=7201973414en_HK

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