INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS

Flexible antennas have revolutionized the wireless communication as integral components of modern smart devices. Their unique properties are design flexibility, enhanced performance, and seamless implementation in smart devices. However, when designing antennas, multiple conflicting objectives ofte...

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Main Authors: Olena Semenova, Andriy Semenov, Stefan Meulesteen, Natalia Kryvinska, Hanna Pastushenko
Format: Article
Language:English
Published: Lublin University of Technology 2024-12-01
Series:Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
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Online Access:https://ph.pollub.pl/index.php/iapgos/article/view/6500
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author Olena Semenova
Andriy Semenov
Stefan Meulesteen
Natalia Kryvinska
Hanna Pastushenko
author_facet Olena Semenova
Andriy Semenov
Stefan Meulesteen
Natalia Kryvinska
Hanna Pastushenko
author_sort Olena Semenova
collection DOAJ
description Flexible antennas have revolutionized the wireless communication as integral components of modern smart devices. Their unique properties are design flexibility, enhanced performance, and seamless implementation in smart devices. However, when designing antennas, multiple conflicting objectives often need to be considered simultaneously. Incorporating artificial neural networks into optimization strategies has shown promising results in antenna design problems. Neural networks can adapt to different and changeable requirements and constraints. That is why they are valuable tools for customizing antennas to specific operating conditions. The utilization of artificial neural networks for the design of flexible antennas enables researchers to expand the design space, optimize antenna characteristics with greater efficiency, and identify innovative solutions that may not be apparent through traditional design methods. In this study, the authors propose to determine required parameters and characteristics of flexible antennas by using Artificial Intelligence techniques, namely fuzzy logic, neural networks, and genetic algorithms. A matching technique based on neural network for designing flexible antennas has been elaborated. A neural network was developed. To train the neural network, several samples of flexible antenna were manufactured and tested. The developed neural network was simulated. Finally, the obtained flexible antenna was tested.
format Article
id doaj-art-347fb75a8a954d3d88422381a9b8ad7e
institution Kabale University
issn 2083-0157
2391-6761
language English
publishDate 2024-12-01
publisher Lublin University of Technology
record_format Article
series Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
spelling doaj-art-347fb75a8a954d3d88422381a9b8ad7e2024-12-22T09:02:18ZengLublin University of TechnologyInformatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska2083-01572391-67612024-12-0114410.35784/iapgos.6500INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNASOlena Semenova0https://orcid.org/0000-0001-5312-9148Andriy Semenov1https://orcid.org/0000-0001-9580-6602Stefan Meulesteen2https://orcid.org/0009-0004-1364-1277Natalia Kryvinska3https://orcid.org/0000-0003-3678-9229Hanna Pastushenko4https://orcid.org/0009-0008-1736-0981Vinnytsia National Technical UniversityVinnytsia National Technical UniversityMontr B.V.Comenius University in BratislavaVinnytsia National Technical University Flexible antennas have revolutionized the wireless communication as integral components of modern smart devices. Their unique properties are design flexibility, enhanced performance, and seamless implementation in smart devices. However, when designing antennas, multiple conflicting objectives often need to be considered simultaneously. Incorporating artificial neural networks into optimization strategies has shown promising results in antenna design problems. Neural networks can adapt to different and changeable requirements and constraints. That is why they are valuable tools for customizing antennas to specific operating conditions. The utilization of artificial neural networks for the design of flexible antennas enables researchers to expand the design space, optimize antenna characteristics with greater efficiency, and identify innovative solutions that may not be apparent through traditional design methods. In this study, the authors propose to determine required parameters and characteristics of flexible antennas by using Artificial Intelligence techniques, namely fuzzy logic, neural networks, and genetic algorithms. A matching technique based on neural network for designing flexible antennas has been elaborated. A neural network was developed. To train the neural network, several samples of flexible antenna were manufactured and tested. The developed neural network was simulated. Finally, the obtained flexible antenna was tested. https://ph.pollub.pl/index.php/iapgos/article/view/6500flexible antennawearable deviceneural network
spellingShingle Olena Semenova
Andriy Semenov
Stefan Meulesteen
Natalia Kryvinska
Hanna Pastushenko
INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
flexible antenna
wearable device
neural network
title INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
title_full INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
title_fullStr INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
title_full_unstemmed INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
title_short INTELLIGENT MATCHING TECHNIQUE FOR FLEXIBLE ANTENNAS
title_sort intelligent matching technique for flexible antennas
topic flexible antenna
wearable device
neural network
url https://ph.pollub.pl/index.php/iapgos/article/view/6500
work_keys_str_mv AT olenasemenova intelligentmatchingtechniqueforflexibleantennas
AT andriysemenov intelligentmatchingtechniqueforflexibleantennas
AT stefanmeulesteen intelligentmatchingtechniqueforflexibleantennas
AT nataliakryvinska intelligentmatchingtechniqueforflexibleantennas
AT hannapastushenko intelligentmatchingtechniqueforflexibleantennas