Designing a Compact Microstrip Antenna Using the Machine Learning Approach

• Autorzy: Sharma Kanhaiya , Pandey Ganga Prasad

Identyfikatory

DOI

10.26636/jtit.2020.143520

• Języki publikacji: EN

Abstrakty

EN

This paper presents how machine learning techniques may be applied in the process of designing a compact dual-band H-shaped rectangular microstrip antenna (RMSA) operating in 0.75–2.20 GHz and 3.0–3.44 GHz frequency ranges. In the design process, the same dimensions of upper and lower notches are incorporated, with the centered position right in the middle. Notch length and width are verified for investigating the antenna. An artificial neural network (ANN) model is developed from the simulated dataset, and is used for shape prediction. The same dataset is used to create a mathematical model as well. The predicted outcome is compared and it is determined that the model relying on ANN offers better results.

Słowa kluczowe

EN

artificial neural network; dual band; microstrip antenna; notch

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2020
• Tom: nr 4
• Strony: 44--52
• Opis fizyczny: Bibliogr. 40 poz., rys., tab.

Twórcy

autor

Sharma Kanhaiya

• Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat 382007, India

autor

Pandey Ganga Prasad

• Department of Information and Communication Technology, School of Technology, Pandit Deendayal Petroleum University, Gandhinagar, Gujarat 382007, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).