A generalized LMI-Based approach to the global asymptotic stability of delayed cellular neural networks
dc.authorscopusid | 7404651584 | |
dc.contributor.author | Singh, V | |
dc.contributor.other | Department of Mechatronics Engineering | |
dc.date.accessioned | 2024-07-05T15:08:36Z | |
dc.date.available | 2024-07-05T15:08:36Z | |
dc.date.issued | 2004 | |
dc.department | Atılım University | en_US |
dc.department-temp | Atilim Univ, Dept Elect Elect Engn, TR-06836 Ankara, Turkey | en_US |
dc.description.abstract | A novel linear matrix inequality (LMI)-based criterion for the global asymptotic stability and uniqueness of the equilibrium point of a class of delayed cellular neural networks (CNNs) is presented. The criterion turns out to be a generalization and improvement over some previous criteria. | en_US |
dc.identifier.citation | 196 | |
dc.identifier.doi | 10.1109/TNN.2003.820616 | |
dc.identifier.endpage | 225 | en_US |
dc.identifier.issn | 1045-9227 | |
dc.identifier.issue | 1 | en_US |
dc.identifier.pmid | 15387264 | |
dc.identifier.scopus | 2-s2.0-1242331018 | |
dc.identifier.startpage | 223 | en_US |
dc.identifier.uri | https://doi.org/10.1109/TNN.2003.820616 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14411/1062 | |
dc.identifier.volume | 15 | en_US |
dc.identifier.wos | WOS:000188603900022 | |
dc.institutionauthor | Sıngh, Vımal | |
dc.language.iso | en | en_US |
dc.publisher | Ieee-inst Electrical Electronics Engineers inc | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | delayed cellular neural networks (DCNNs) | en_US |
dc.subject | equilibrium analysis | en_US |
dc.subject | global stability | en_US |
dc.title | A generalized LMI-Based approach to the global asymptotic stability of delayed cellular neural networks | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | e3234b4c-8993-4550-93fe-38796ff7c7e1 | |
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