Title :
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
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;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2013.2283022
