A Novel Electromagnetic Interference Source Reconstruction Method based on Artificial Neural Network
| Autor: | Yu-Han Zhong, Ze-Kai Hu, Yu-Fei Shu, Xing-Chang Wei, Yi-Wen Wang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
Physics Artificial neural network Field (physics) Iterative method Acoustics 020206 networking & telecommunications 02 engineering and technology 01 natural sciences Noise (electronics) Electromagnetic interference Magnetic field Dipole 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Magnetic dipole |
| Zdroj: | 2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE). |
| DOI: | 10.1109/isape.2018.8634161 |
| Popis: | This paper discusses an equivalent magnetic dipoles hybrid with artificial neural network method to reconstruct the noise source. The original near-field of the real source is obtained through the near-field scanning, and then the equivalent magnetic dipoles source is constructed to predict the radiation from the real source. The information of field's amplitude and phase is used to find the magnetic moment and locations of the equivalent dipoles. An iterative method combined with the artificial neural network is proposed for this purpose, where the origin field is continuously subtracted from the new field generated by equivalent magnetic dipoles. Through numerical and experimental results, the accuracy and efficiency of the proposed method are verified. |
| Databáze: | OpenAIRE |
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