dc.contributor.author | FAYDASIÇOK, Özlem | |
dc.date.accessioned | 2021-03-02T17:08:20Z | |
dc.date.available | 2021-03-02T17:08:20Z | |
dc.identifier.citation | FAYDASIÇOK Ö., "A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays", NEURAL NETWORKS, cilt.129, ss.288-297, 2020 | |
dc.identifier.issn | 0893-6080 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.other | av_eed625ce-7aa2-4ae3-a0f3-36cd6d518d39 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/3647 | |
dc.identifier.uri | https://doi.org/10.1016/j.neunet.2020.06.013 | |
dc.description.abstract | This research paper conducts an investigation into the stability issue for a more general class of neutral-type Hopfield neural networks that involves multiple time delays in the states of neurons and multiple neutral delays in the time derivatives of the states of neurons. By constructing a new proper Lyapunov functional, an alternative easily verifiable algebraic criterion for global asymptotic stability of this type of Hopfield neural systems is derived. This new stability condition is entirely independent of time and neutral delays. Two instructive examples are employed to indicate that the result obtained in this paper reveals a new set of sufficient stability criteria when it is compared with the previously reported stability results. Therefore, the proposed stability result enlarges the application domain of Hopfield neural systems of neutral types. (C) 2020 Elsevier Ltd. All rights reserved. | |
dc.language.iso | eng | |
dc.subject | Cellular and Molecular Neuroscience | |
dc.subject | Cognitive Neuroscience | |
dc.subject | General Neuroscience | |
dc.subject | Neuroscience (miscellaneous) | |
dc.subject | Sensory Systems | |
dc.subject | Artificial Intelligence | |
dc.subject | General Computer Science | |
dc.subject | Human-Computer Interaction | |
dc.subject | Computer Science (miscellaneous) | |
dc.subject | Computer Vision and Pattern Recognition | |
dc.subject | Physical Sciences | |
dc.subject | Life Sciences | |
dc.subject | Computer Science Applications | |
dc.subject | BİLGİSAYAR BİLİMİ, YAPAY ZEKA | |
dc.subject | Bilgisayar Bilimi | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | NEUROSCIENCES | |
dc.subject | Sinirbilim ve Davranış | |
dc.subject | Yaşam Bilimleri (LIFE) | |
dc.subject | Bilgisayar Bilimleri | |
dc.subject | Algoritmalar | |
dc.subject | Yaşam Bilimleri | |
dc.subject | Temel Bilimler | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Developmental Neuroscience | |
dc.title | A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays | |
dc.type | Makale | |
dc.relation.journal | NEURAL NETWORKS | |
dc.contributor.department | İstanbul Üniversitesi , Fen Fakültesi , Matematik Bölümü | |
dc.identifier.volume | 129 | |
dc.identifier.startpage | 288 | |
dc.identifier.endpage | 297 | |
dc.contributor.firstauthorID | 2489863 | |