Global Robust Stability of Delayed Neural Networks: an Lmi Approach

dc.contributor.author Singh, V
dc.contributor.other Department of Mechatronics Engineering
dc.contributor.other 01. Atılım University
dc.date.accessioned 2024-07-05T15:09:41Z
dc.date.available 2024-07-05T15:09:41Z
dc.date.issued 2005
dc.description.abstract New criteria for the uniqueness and global robust stability of the equilibrium point of the interval Hopfield-type delayed neural networks are presented. The criteria possess the structure of linear matrix inequality and, hence, are computationally efficient. en_US
dc.identifier.doi 10.1109/TCSII.2004.840118
dc.identifier.issn 1057-7130
dc.identifier.scopus 2-s2.0-12544252350
dc.identifier.uri https://doi.org/10.1109/TCSII.2004.840118
dc.identifier.uri https://hdl.handle.net/20.500.14411/1223
dc.language.iso en en_US
dc.publisher Ieee-inst Electrical Electronics Engineers inc en_US
dc.relation.ispartof IEEE Transactions on Circuits and Systems II: Express Briefs
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject dynamical interval neural networks en_US
dc.subject equilibrium analysis en_US
dc.subject global robust stability en_US
dc.title Global Robust Stability of Delayed Neural Networks: an Lmi Approach en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Sıngh, Vımal
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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 36 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.startpage 33 en_US
gdc.description.volume 52 en_US
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gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
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gdc.opencitations.count 116
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