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

Creator:

Sharma, Kanhaiya ; Pandey, Ganga Prasad

Date:

2020, nr 4

Resource Type:

artykuł

Description:

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

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2157

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

artificial neural networks microstrip antenna dual band notch

Object collections:

Last modified:

Jan 27, 2021

In our library since:

Jan 27, 2021

Number of object content hits:

49

All available object's versions:

https://ribes-54.man.poznan.pl/publication/2455

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Edition name Date
Sharma, Kanhaiya; Pandey, Ganga Prasad, Designing a Compact Microstrip Antenna Using the Machine Learning Approach, Journal of Telecommunications and Information Technology, 2020, nr 4 Jan 27, 2021

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(+48) 5128 696

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