A New Neural Predictor for ELF Magnetic Field Strength

被引：7

作者：

Coco, Salvatore ^{[1
]}

Laudani, Antonino ^{[2
]}

Fulginei, Francesco Riganti ^{[2
]}

Salvini, Alessandro ^{[2
]}

机构：

[1] Univ Catania, DIEEI, I-95125 Catania, Italy

[2] Univ Roma Tre, Dept Engn, I-00146 Rome, Italy

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2014年 / 50卷 / 02期

关键词：

Artificial neural networks (NNs); magnetic field measurement; magnetic shielding; predictive models; MODEL;

D O I：

10.1109/TMAG.2013.2283022

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：69 / 72

页数：4

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