Integrated Circuit Radiation Source Reconstruction Method Based on Deep Neural Network

Conventional electromagnetic radiation analysis techniques struggle to accurately predict radiation sources in the increasingly complex electromagnetic environment. This paper proposes a novel electromagnetic radiation source reconstruction method based on deep neural network (DNN). This method maps near-field data to electromagnetic dipoles and can automatically adjusts parameters to accommodate near-field data with different structures. It effectively addresses the ill-conditioned matrix issue inherent in traditional approaches and eliminates the need for specific initial values, unlike other algorithms. Simulation results show that the proposed method precisely reconstructs the radiation source characteristics of complex systems in RF and microwave circuits, offering valuable insights and practical tools for electromagnetic compatibility (EMC) design in integrated circuits.