A Generalized Lmi-Based Approach To the Global Asymptotic Stability of Delayed Cellular Neural Networks
| dc.contributor.author | Singh, V | |
| dc.contributor.other | Department of Mechatronics Engineering | |
| dc.contributor.other | 01. Atılım University | |
| dc.date.accessioned | 2024-07-05T15:08:36Z | |
| dc.date.available | 2024-07-05T15:08:36Z | |
| dc.date.issued | 2004 | |
| 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.doi | 10.1109/TNN.2003.820616 | |
| dc.identifier.issn | 1045-9227 | |
| dc.identifier.scopus | 2-s2.0-1242331018 | |
| dc.identifier.uri | https://doi.org/10.1109/TNN.2003.820616 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/1062 | |
| dc.language.iso | en | en_US |
| dc.publisher | Ieee-inst Electrical Electronics Engineers inc | en_US |
| dc.relation.ispartof | IEEE Transactions on Neural Networks | |
| 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 | |
| gdc.author.institutional | Sıngh, Vımal | |
| gdc.author.scopusid | 7404651584 | |
| gdc.bip.impulseclass | C3 | |
| gdc.bip.influenceclass | C3 | |
| gdc.bip.popularityclass | C4 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.description.department | Atılım University | en_US |
| gdc.description.departmenttemp | Atilim Univ, Dept Elect Elect Engn, TR-06836 Ankara, Turkey | en_US |
| gdc.description.endpage | 225 | en_US |
| gdc.description.issue | 1 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 223 | en_US |
| gdc.description.volume | 15 | en_US |
| gdc.identifier.openalex | W2111906242 | |
| gdc.identifier.pmid | 15387264 | |
| gdc.identifier.wos | WOS:000188603900022 | |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 67.0 | |
| gdc.oaire.influence | 2.7774863E-8 | |
| gdc.oaire.isgreen | false | |
| gdc.oaire.keywords | Linear Models | |
| gdc.oaire.keywords | Neural Networks, Computer | |
| gdc.oaire.popularity | 8.818342E-9 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0209 industrial biotechnology | |
| gdc.oaire.sciencefields | 0202 electrical engineering, electronic engineering, information engineering | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
| gdc.openalex.fwci | 23.612 | |
| gdc.openalex.normalizedpercentile | 0.96 | |
| gdc.openalex.toppercent | TOP 10% | |
| gdc.opencitations.count | 191 | |
| gdc.plumx.crossrefcites | 191 | |
| gdc.plumx.mendeley | 1 | |
| gdc.plumx.scopuscites | 211 | |
| gdc.scopus.citedcount | 211 | |
| gdc.wos.citedcount | 193 | |
| relation.isAuthorOfPublication | e3234b4c-8993-4550-93fe-38796ff7c7e1 | |
| relation.isAuthorOfPublication.latestForDiscovery | e3234b4c-8993-4550-93fe-38796ff7c7e1 | |
| relation.isOrgUnitOfPublication | e2a6d0b1-378e-4532-82b1-d17cabc56744 | |
| relation.isOrgUnitOfPublication | 50be38c5-40c4-4d5f-b8e6-463e9514c6dd | |
| relation.isOrgUnitOfPublication.latestForDiscovery | e2a6d0b1-378e-4532-82b1-d17cabc56744 |