3 papers
eess.SP2026
Geometry-Decoupled Deep Unfolding for Gridless Super-Resolution TomoSAR Under Nonuniform Baselines
Kun Qian, Zhuge Xia, Qian Ma +2
Super-resolution SAR tomography (TomoSAR) is performed on a discretized elevation grid, leading to off-grid bias and spectral leakage. Classical Toeplitz-Vandermonde gridless formu…
eess.SP2025
DeltaDPD: Exploiting Dynamic Temporal Sparsity in Recurrent Neural Networks for Energy-Efficient Wideband Digital Predistortion
Yizhuo Wu, Yi Zhu, Kun Qian +5
Digital Predistortion (DPD) is a popular technique to enhance signal quality in wideband RF power amplifiers (PAs). With increasing bandwidth and data rates, DPD faces significant…
cs.LG2024
Investigating KAN-Based Physics-Informed Neural Networks for EMI/EMC Simulations
Kun Qian, Mohamed Kheir
The main objective of this paper is to investigate the feasibility of employing Physics-Informed Neural Networks (PINNs) techniques, in particular KolmogorovArnold Networks (KANs),…