Lmi Approach To the Global Robust Stability of a Larger Class of Neural Networks With Delay
| dc.contributor.author | Singh, Vimal | |
| dc.date.accessioned | 2024-07-05T14:33:22Z | |
| dc.date.available | 2024-07-05T14:33:22Z | |
| dc.date.issued | 2007 | |
| dc.description.abstract | Sufficient conditions in the form of linear matrix inequality for the uniqueness and global asymptotic stability of the equilibrium point of a large class of uncertain neural networks with delay are presented. The conditions are based on norm-bounded uncertainties. An example is given to show the effectiveness of the obtained results. A comparison is made between the present approach and an earlier approach due to Lu, Rong and Chen. An error is corrected in an earlier publication. (c) 2006 Elsevier Ltd. All rights reserved. | en_US |
| dc.identifier.doi | 10.1016/j.chaos.2006.01.001 | |
| dc.identifier.issn | 0960-0779 | |
| dc.identifier.issn | 1873-2887 | |
| dc.identifier.scopus | 2-s2.0-33846397144 | |
| dc.identifier.uri | https://doi.org/10.1016/j.chaos.2006.01.001 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/925 | |
| dc.language.iso | en | en_US |
| dc.publisher | Pergamon-elsevier Science Ltd | en_US |
| dc.relation.ispartof | Chaos, Solitons & Fractals | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | [No Keyword Available] | en_US |
| dc.title | Lmi Approach To the Global Robust Stability of a Larger Class of Neural Networks With Delay | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.scopusid | 7404651584 | |
| gdc.bip.impulseclass | C4 | |
| gdc.bip.influenceclass | C4 | |
| gdc.bip.popularityclass | C5 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.collaboration.industrial | false | |
| 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 | 1934 | en_US |
| gdc.description.issue | 5 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 1927 | en_US |
| gdc.description.volume | 32 | en_US |
| gdc.description.wosquality | Q1 | |
| gdc.identifier.openalex | W1981861103 | |
| gdc.identifier.wos | WOS:000244504000035 | |
| gdc.index.type | WoS | |
| gdc.index.type | Scopus | |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 13.0 | |
| gdc.oaire.influence | 3.7243453E-9 | |
| gdc.oaire.isgreen | false | |
| gdc.oaire.keywords | Stability theory of functional-differential equations | |
| gdc.oaire.keywords | robust stability | |
| gdc.oaire.keywords | delay equations | |
| gdc.oaire.keywords | Robust stability | |
| gdc.oaire.keywords | Neural networks for/in biological studies, artificial life and related topics | |
| gdc.oaire.keywords | neural networks | |
| gdc.oaire.popularity | 8.3836166E-10 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0103 physical sciences | |
| gdc.oaire.sciencefields | 0202 electrical engineering, electronic engineering, information engineering | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
| gdc.oaire.sciencefields | 01 natural sciences | |
| gdc.openalex.collaboration | National | |
| gdc.openalex.fwci | 4.19891421 | |
| gdc.openalex.normalizedpercentile | 0.91 | |
| gdc.openalex.toppercent | TOP 10% | |
| gdc.opencitations.count | 13 | |
| gdc.plumx.crossrefcites | 13 | |
| gdc.plumx.mendeley | 10 | |
| gdc.plumx.scopuscites | 15 | |
| gdc.scopus.citedcount | 15 | |
| gdc.virtual.author | Sıngh, Vımal | |
| gdc.wos.citedcount | 14 | |
| 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 |