Global Robust Stability of Delayed Neural Networks: an Lmi Approach

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dc.authorscopusid7404651584
dc.contributor.authorSingh, V
dc.contributor.authorSıngh, Vımal
dc.contributor.otherDepartment of Mechatronics Engineering
dc.date.accessioned2024-07-05T15:09:41Z
dc.date.available2024-07-05T15:09:41Z
dc.date.issued2005
dc.departmentAtılım Universityen_US
dc.department-tempAtilim Univ, Dept Elect Elect Engn, TR-06836 Ankara, Turkeyen_US
dc.description.abstractNew criteria for the uniqueness and global robust stability of the equilibrium point of the interval Hopfield-type delayed neural networks are presented. The criteria possess the structure of linear matrix inequality and, hence, are computationally efficient.en_US
dc.identifier.citation121
dc.identifier.doi10.1109/TCSII.2004.840118
dc.identifier.endpage36en_US
dc.identifier.issn1057-7130
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-12544252350
dc.identifier.startpage33en_US
dc.identifier.urihttps://doi.org/10.1109/TCSII.2004.840118
dc.identifier.urihttps://hdl.handle.net/20.500.14411/1223
dc.identifier.volume52en_US
dc.identifier.wosWOS:000226221000007
dc.language.isoenen_US
dc.publisherIeee-inst Electrical Electronics Engineers incen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdynamical interval neural networksen_US
dc.subjectequilibrium analysisen_US
dc.subjectglobal robust stabilityen_US
dc.titleGlobal Robust Stability of Delayed Neural Networks: an Lmi Approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
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