This paper studies the problem of accurately recovering a structured signal from a small
number of corrupted sub-Gaussian measurements. We consider three different procedures …

Corrupted sensing concerns the problem of recovering a high-dimensional structured signal
from a collection of measurements that are contaminated by unknown structured corruption …

The reliable characterization of quantum states as well as any potential noise in various
quantum systems is crucial for advancing quantum technologies. In this work we propose …

惩罚优化问题常常用于在有噪声的条件下用较少的观测个数来求解线性逆问题. 目前,
对惩罚优化问题恢复误差的研究主要存在以下两点不足: 一是对权重参数往往有要求; …

In [1], a sharp phase transition has been numerically observed when a constrained convex
procedure is used to solve the corrupted sensing problem. In this paper, we present a …

This paper studies the problem of recovering a structured signal from a relatively small
number of corrupted non-linear measurements. Assuming that signal and corruption are …

This paper is concerned with the problem of recovering a structured signal from a relatively
small number of corrupted random measurements. Sharp phase transitions have been …

In this letter, we characterize a data-time tradeoff for projected gradient descent (PGD)
algorithms used for solving corrupted sensing problems under sub-Gaussian …

The problem of corrupted sensing aims to recover a signal from corrupted measurements.
As a result of the ill-posedness of the problem, recovery is impossible for arbitrary signal and …

Penalized programs are widely used to solve linear inverse problems in the presence of
noise. For now, the study of the performance of panelized programs has two disadvantages …