Next-Generation Solvers for Complex Microwave Engineering Problems

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This project aims to design a complementary physics-guided, data-driven method that can accurately solve complex microwave engineering problems in a timely manner. The primary bottleneck so far preventing that approach, which is the disparity between the trained theoretical model and reality, will be overcome using a multi-frequency complex-valued domain adaptation technique. The method will use deep neural networks to reliably learn the physical concepts of microwave engineering problems. This project will have significant economic and societal benefits, such as supporting the efficient design, installation and operation of communication systems, mining, infrastructure inspection, security, remote sensing, and microwave imaging.