Investigating KAN-Based Physics-Informed Neural Networks for EMI/EMC Simulations

Understand

The main objective of this paper is to investigate the feasibility of employing Physics-Informed Neural Networks (PINNs) techniques, in particular KolmogorovArnold Networks (KANs), for facilitating Electromagnetic Interference (EMI) simulations.

• It introduces some common EM problem formulations and how they can be solved using AI-driven solutions instead of lengthy and complex full-wave numerical simulations.
• This research may open new horizons for green EMI simulation workflows with less energy consumption and feasible computational capacity.