Estimating Far-Field Emissions From Simulated Near-Field Data With Artificial Neural Networks

Author

Firmino, Luciana ; Raizer, Adroaldo ; MARECHAL, Yves

Author_Institution

Fed. Univ. of Santa Catarina, Florianopolis, Brazil

Volume

50

Issue

2

fYear

2014

fDate

Feb. 2014

Firstpage

205

Lastpage

208

Abstract

In this paper, a procedure for estimating the electromagnetic fields radiated far from their source based on near-field (NF) simulation is considered. The NFs radiated from the sources are modeled with the transmission-line matrix method. The so-called far fields are estimated with the help of different artificial neural networks. Comparison with results based on theoretical equations and software simulations substantiate the validity of the proposed method association.

Keywords

dipole antennas; electrical engineering computing; loop antennas; neural nets; ANN; EM field; EM source; Hertzian dipole; artificial neural networks; complex antennas; electromagnetic fields; far-field emissions estimation; loop antennas; near-field data; near-field simulation; outward radiation; software simulations; theoretical equations; transmission-line matrix method; Antenna measurements; Artificial neural networks; Mathematical model; Neurons; Noise measurement; Numerical models; Time-domain analysis; Antennas and propagation; artificial neural networks (ANNs); computational electromagnetics (EMs); transmission-line matrix methods;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2013.2282354

Filename

6749022