A New Neural Predictor for ELF Magnetic Field Strength

Author

Coco, S. ; Laudani, Antonino ; Fulginei, Francesco Riganti ; Salvini, Alessandro

Author_Institution

DIEEI, Univ. of Catania, Catania, Italy

Volume

50

Issue

2

fYear

2014

fDate

Feb. 2014

Firstpage

69

Lastpage

72

Abstract

A new neural predictor (NP) is presented for the evaluation of the magnetic field distribution at extremely low frequency in indoor or outdoor environments. The NP uses a reduced number of measurements and performs the evaluation of the magnetic field strength in the environment under analysis, by achieving a high degree of immunity to the noise present in the measurements. To achieve good performance, ad hoc strategies have been adopted for the setup and the neural network training. The NP has been tested on a real environment and the obtained results exhibit a close agreement with the measured field values.

Keywords

ad hoc networks; indoor environment; magnetic fields; neural nets; ELF magnetic field strength; ad hoc strategy; indoor environments; magnetic field distribution; neural network training; neural predictor; outdoor environments; Artificial neural networks; Computational modeling; Geophysical measurement techniques; Ground penetrating radar; Magnetic moments; Noise; Training; Artificial neural networks (NNs); magnetic field measurement; magnetic shielding; predictive models;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2013.2283022

Filename

6749079