The Prediction of Magnetic Near-Field Distribution Characteristics Based on Artificial Neural Network

In this paper, the magnetic near-field distribution characteristics of a printed circuit board (PCB) are predicted based on developed artificial neural networks (ANNs). ANN is capable of understanding how the trend of the radiation nearfield varies when a PCB working at adjacent different frequencies, making the near-field prediction possess with higher accuracy and lower time-cost. The proposed method offers a fresh perspective on how to analyze the near-field distribution characteristics in electromagnetic compatibility (EMC) issues.