21 citations · 26 across the 3 of their papers we have counts for
3 papers
math.NA2023
Sorted L1/L2 Minimization for Sparse Signal Recovery
Chao Wang, Ming Yan, Junjie Yu
This paper introduces a novel approach for recovering sparse signals using sorted L1/L2 minimization. The proposed method assigns higher weights to indices with smaller absolute va…
cs.IT2018★ 5 cited
Fast Signal Recovery from Saturated Measurements by Linear Loss and Nonconvex Penalties
Fan He, Xiaolin Huang, Yipeng Liu +1
Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recov…
math.OC2014★ 21 cited
Nonconvex Sorted Minimization for Sparse Approximation
Xiaolin Huang, Lei Shi, Ming Yan
The norm is the tight convex relaxation for the "norm" and has been successfully applied for recovering sparse signals. For problems with fewer samplings, one nee…