Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1941
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dc.contributor.authorNakmouche, Mohammed Farouk-
dc.contributor.authorAllam, A. M. M. A.-
dc.contributor.authorFawzy, Diaa E.-
dc.contributor.authorLin, Ding Bing-
dc.date.accessioned2023-06-16T14:25:24Z-
dc.date.available2023-06-16T14:25:24Z-
dc.date.issued2021-
dc.identifier.isbn978-1-6654-4071-4-
dc.identifier.urihttps://doi.org/10.1109/ICEEE52452.2021.9415911-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/1941-
dc.description8th International Conference on Electrical and Electronics Engineering (ICEEE) -- APR 09-11, 2021 -- Antalya, TURKEYen_US
dc.description.abstractIn this manuscripts, H-slotted DGS based antenna configuration for K/Ku applications is designed, fabricated and measured using ROHDE & SCHWARZ ZVB20 network analyzer. Simulation studies are performed using Electromagnetic Simulation Software CST Studio Suite. Moreover, a development of Artificial Neural Networks (ANN) model is implemented based on feed-forward back-propagation and Bayesian regularization learning algorithm. The optimal position for H-slotted DGS antenna performance is predicted in terms of reflection coefficient and resonance frequency. The antenna is implemented on Rogers RT/Duroid 5880 with relative dielectric constant of 0.0009 and thickness 0.38 mm. It operates at both 15.04 GHz (from 14.87 GHz to 15.208 GHz) and 24.77 GHz (from 24.404 GHz to 25.137 GHz). The antenna achieves gains of 5.59 dB and 6.10 dB and efficiencies of 87 % and 80 % at both frequencies, respectively. The simulation using CST, predicted ANN and measurement results are in good agreement.en_US
dc.description.sponsorshipIEEEen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 8Th Internatıonal Conference on Electrıcal And Electronıcs Engıneerıng (Iceee 2021)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmicrostrip antennaen_US
dc.subjectdefected ground structure (DGS)en_US
dc.subjectfinite element methodsen_US
dc.subjectartificial neural networks (ANN)en_US
dc.subjectCST studio suiteen_US
dc.subject5G banden_US
dc.subjectdual banden_US
dc.subjectlow profileen_US
dc.subjectArrayen_US
dc.titleLow Profile Dual Band H-Slotted DGS Based Antenna Design Using ANN for K/Ku Band Applicationsen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/ICEEE52452.2021.9415911-
dc.identifier.scopus2-s2.0-85106499886en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorscopusid57206657916-
dc.authorscopusid55582327600-
dc.authorscopusid23011278600-
dc.authorscopusid7403692642-
dc.identifier.startpage283en_US
dc.identifier.endpage286en_US
dc.identifier.wosWOS:000719372400052en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.grantfulltextreserved-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
crisitem.author.dept05.01. Aerospace Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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