dc.contributor.author | Faydasıçok, Özlem | en_US |
dc.contributor.author | Arık, Sabri | en_US |
dc.date.accessioned | 2015-01-15T23:02:05Z | |
dc.date.available | 2015-01-15T23:02:05Z | |
dc.date.issued | 2012-02-15 | |
dc.identifier.citation | Faydasıçok, Ö. & Arık, S. (2012). Equilibrium and stability analysis of delayed neural networks under parameter uncertainties. Applied Mathematics and Computation, 218(12), 6716-6726. doi:10.1016/j.amc.2011.12.036 | en_US |
dc.identifier.issn | 0096-3003 | |
dc.identifier.issn | 1873-5649 | |
dc.identifier.uri | https://hdl.handle.net/11729/456 | |
dc.identifier.uri | http://dx.doi.org/10.1016/j.amc.2011.12.036 | |
dc.description.abstract | This paper proposes new results for the existence, uniqueness and global asymptotic stability of the equilibrium point for neural networks with multiple time delays under parameter uncertainties. By using Lyapunov stability theorem and applying homeomorphism mapping theorem, new delay-independent stability criteria are obtained. The obtained results are in terms of network parameters of the neural system only and therefore they can be easily checked. We also present some illustrative numerical examples to demonstrate that our result are new and improve corresponding results derived in the previous literature. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier Science Inc | en_US |
dc.relation.isversionof | 10.1016/j.amc.2011.12.036 | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Mathematics | en_US |
dc.subject | Stability analysis | en_US |
dc.subject | Delayed neural networks | en_US |
dc.subject | Interval matrices | en_US |
dc.subject | Lyapunov functionals | en_US |
dc.subject | Time-varying delays | en_US |
dc.subject | Global robust stability | en_US |
dc.subject | Exponential stability | en_US |
dc.subject | Distributed delays | en_US |
dc.subject | Neutral-type | en_US |
dc.subject | Discrete | en_US |
dc.subject | Criteria | en_US |
dc.title | Equilibrium and stability analysis of delayed neural networks under parameter uncertainties | en_US |
dc.type | article | en_US |
dc.description.version | Publisher's Version | en_US |
dc.relation.journal | Applied Mathematics and Computation | en_US |
dc.contributor.department | Işık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.contributor.department | Işık University, Faculty of Engineering, Department of Electrical-Electronics Engineering | en_US |
dc.contributor.authorID | 0000-0002-4390-5139 | |
dc.identifier.volume | 218 | |
dc.identifier.issue | 12 | |
dc.identifier.startpage | 6716 | |
dc.identifier.endpage | 6726 | |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.institutionauthor | Arık, Sabri | en_US |
dc.relation.index | WOS | en_US |
dc.relation.index | Scopus | en_US |
dc.relation.index | Science Citation Index Expanded (SCI-EXPANDED) | en_US |
dc.description.quality | Q1 | |
dc.description.wosid | WOS:000299847700011 | |