Intelligent matching technique for flexible antennas

• Autorzy: Semenova Olena , Semenov Andriy , Meulesteen Stefan , Pastushenko Hanna , Kryvinska Natalia

Identyfikatory

DOI

10.35784/iapgos.6500

Warianty tytułu

PL

Inteligentna technologia dopasowywania dla elastycznych anten

• Języki publikacji: EN

Abstrakty

EN

Flexible antennas have revolutionized the wireless communication asintegral componentsof modern smart devices. Their unique propertiesare 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 resultsin antenna design problems. Neural networks canadapt to different and changeable requirements and constraints. That is why they arevaluable toolsfor 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 requiredparameters and characteristics of flexible antennas by using Artificial Intelligence techniques, namely fuzzy logic, neural networks, and genetic algorithms. Amatching technique based on neural networkfor 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.

PL

Elastyczne anteny zrewolucjonizowały komunikację bezprzewodową jako integralny element nowoczesnych inteligentnych urządzeń.Ich unikalne właściwości obejmują większą elastyczność projektowania, zwiększoną wydajność i bezproblemowe wdrażanie w inteligentnych urządzeniach.Jednak przy projektowaniu anten często konieczne jest jednoczesne uwzględnienie kilku celów, które są ze sobą sprzeczne. Zastosowanie sztucznych sieci neuronowych w strategii optymalizacji dało już obiecujące wyniki w problematyce projektowania anten. Sieci neuronowe potrafią dostosowywać siędo zmieniających się wymagań i ograniczeń. Dlatego są one cennym narzędziem do dostrajania antendo konkretnych warunków pracy.Wykorzystanie sztucznych sieci neuronowych do projektowania elastycznych anten pozwala naukowcom rozszerzyć przestrzeń projektową, zoptymalizować charakterystykę anteny z większą wydajnością i ujawnić innowacyjne rozwiązania, które mogą nie być oczywiste przy użyciu tradycyjnych metod projektowania.W pracy autorzy proponują wyznaczenie niezbędnych parametrów i charakterystyk elastycznych anten z wykorzystaniem metod sztucznej inteligencji, czyli logiki rozmytej, sieci neuronowych i algorytmów genetycznych. Opracowano technikę dopasowywania opartą na sieci neuronowejdo projektowania elastycznych anten. Opracowano sieć neuronową. Wyprodukowano i przetestowano kilka próbek elastycznych antenna potrzeby uczenia sieci neuronowej. Wykonano symulację opracowanej sieci neuronowej. Na koniec przetestowano powstałą elastyczną antenę.

Słowa kluczowe

EN

flexible antenna; wearable device; neural network

PL

antena elastyczna; urządzenie ubieralne; sieć neuronowa

• Wydawca: Wydawnictwo Politechniki Lubelskiej
• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2024
• Tom: T. 14, nr 4
• Strony: 16--22
• Opis fizyczny: Bibliogr. 32 poz., rys., tab.

Twórcy

autor

Semenova Olena

• Vinnytsia National Technical University, Faculty of Informational Electronic Systems, Vinnytsia, Ukraine

• https://orcid.org/0000-0001-5312-9148

autor

Semenov Andriy

• Vinnytsia National Technical University, Faculty of Informational Electronic Systems, Vinnytsia, Ukraine

• https://orcid.org/0000-0001-9580-6602

autor

Meulesteen Stefan

• Montr B.V., Hague, Netherlands

• https://orcid.org/0009-0004-1364-1277

autor

Pastushenko Hanna

• Vinnytsia National Technical University, Faculty of Informational Electronic Systems, Vinnytsia, Ukraine

• https://orcid.org/0009-0008-1736-0981

autor

Kryvinska Natalia

• University in Bratislava, Department of Information Management and Business Systems, Bratislava, Slovakia

• https://orcid.org/0000-0003-3678-9229

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