3 papers
physics.comp-ph2026
Coordinate-Residual Physics-Driven Neural Network for Electromagnetic Inverse Scattering
Yutong Du, Zicheng Liu, Bo Qi +2
Electromagnetic inverse scattering is a nonlinear and ill-posed problem, where accurate reconstruction is challenging due to measurement limitations, noise, and high computational…
physics.app-ph2025
Field Reconstruction for High-Frequency Electromagnetic Exposure Assessment Based on Deep Learning
Miao Cao, Zicheng Liu, Bazargul Matkerim +4
Fifth-generation (5G) communication systems, operating in higher frequency bands from 3 to 300 GHz, provide unprecedented bandwidth to enable ultra-high data rates and low-latency…
eess.IV2025
Quality-factor inspired deep neural network solver for solving inverse scattering problems
Yutong Du, Zicheng Liu, Miao Cao +3
Deep neural networks have been applied to address electromagnetic inverse scattering problems (ISPs) and shown superior imaging performances, which can be affected by the training…