Tytuł:

Designing a Compact Microstrip Antenna Using the Machine Learning Approach, Journal of Telecommunications and Information Technology, 2020, nr 4

Autor:

Sharma, Kanhaiya ; Pandey, Ganga Prasad

Temat i słowa kluczowe:

artificial neural networks ; microstrip antenna ; dual band ; notch

Opis:

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

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Data wydania:

2020, nr 4

Typ zasobu:

artykuł

Format:

application/pdf

Identyfikator zasobu:

ISSN 1509-4553, on-line: ISSN 1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności