Deep Learning: A New Era in Electromagnetics (Review Article)
Ahmed Mohamed Attiya, Taspia Salam · 2025
This paper provides a comprehensive review of the application of deep learning techniques to solve electromagnetic wave problems. It begins with a brief historical overview of electromagnetics, highlighting the connections between different eras. The fundamental principles of neural networks and deep learning are then introduced. Subsequently, several illustrative examples are presented to demonstrate the application of deep learning in electromagnetics, including direction-of-arrival estimation, beamforming, microwave imaging, and path loss prediction. Furthermore, emerging trends in the use of deep learning for electromagnetic wave problems are discussed, offering insights into potential future research directions in this rapidly evolving field.