Simplified Approach To the Exponential Stability of Delayed Neural Networks With Time Varying Delays
dc.authorscopusid | 7404651584 | |
dc.contributor.author | Singh, Vimal | |
dc.contributor.other | Department of Mechatronics Engineering | |
dc.date.accessioned | 2024-07-05T14:33:48Z | |
dc.date.available | 2024-07-05T14:33:48Z | |
dc.date.issued | 2007 | |
dc.department | Atılım University | en_US |
dc.department-temp | Atilim Univ, Dept Elect Elect Engn, TR-06836 Ankara, Turkey | en_US |
dc.description.abstract | Sufficient conditions in the form of linear matrix inequalities for the exponential stability of the equilibrium point for delayed neural networks with time varying delays are presented. The conditions turn out to be greatly simplified versions of the exponential stability results previously reported by Yucel and Arik. A distinct feature of the present criteria is that they are free of the degree of exponential stability. This feature makes the criteria computationally very attractive. (c) 2005 Elsevier Ltd. All rights reserved. | en_US |
dc.identifier.citationcount | 8 | |
dc.identifier.doi | 10.1016/j.chaos.2005.11.006 | |
dc.identifier.endpage | 616 | en_US |
dc.identifier.issn | 0960-0779 | |
dc.identifier.issn | 1873-2887 | |
dc.identifier.issue | 2 | en_US |
dc.identifier.scopus | 2-s2.0-33749557213 | |
dc.identifier.startpage | 609 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.chaos.2005.11.006 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14411/956 | |
dc.identifier.volume | 32 | en_US |
dc.identifier.wos | WOS:000242759600040 | |
dc.identifier.wosquality | Q1 | |
dc.institutionauthor | Sıngh, Vımal | |
dc.language.iso | en | en_US |
dc.publisher | Pergamon-elsevier Science Ltd | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.scopus.citedbyCount | 7 | |
dc.subject | [No Keyword Available] | en_US |
dc.title | Simplified Approach To the Exponential Stability of Delayed Neural Networks With Time Varying Delays | en_US |
dc.type | Article | en_US |
dc.wos.citedbyCount | 8 | |
dspace.entity.type | Publication | |
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