activity
20172020
most citedThe perturbation analysis of nonconvex low-rank matrix robust recovery

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.IT2020

The high-order block RIP for non-convex block-sparse compressed sensing

Jianwen Huang, Xinling Liu, Jinyao Hou +1

This paper concentrates on the recovery of block-sparse signals, which is not only sparse but also nonzero elements are arrayed into some blocks (clusters) rather than being arbitr…

cs.IT20201 cited

The perturbation analysis of nonconvex low-rank matrix robust recovery

Jianwen Huang, Wendong Wang, Feng Zhang +1

In this paper, we bring forward a completely perturbed nonconvex Schatten -minimization to address a model of completely perturbed low-rank matrix recovery. The paper that based…

cs.IT2020

An Optimal Condition of Robust Low-rank Matrices Recovery

Jianwen Huang, Jianjun Wang, Feng Zhang +1

In this paper we investigate the reconstruction conditions of nuclear norm minimization for low-rank matrix recovery. We obtain sufficient conditions with $0<t<4/3…

math.PR2020

Expansions of maximum and minimum from Generalized Maxwell distribution

Jianwen Huang

Generalized Maxwell distribution is an extension of the classic Maxwell distribution. In this paper, we concentrate on the joint distributional asymptotics of normalized maxima and…

math.PR2020

On the distributional expansions of powered extremes from Maxwell distribution

Jianwen Huang, Xinling Liu, Jianjun Wang +3

In this paper, asymptotic expansions of the distributions and densities of powered extremes for Maxwell samples are considered. The results show that the convergence speeds of norm…

cs.IT2020

An analysis of noise folding for low-rank matrix recovery

Jianwen Huang, Jianjun Wang, Feng Zhang +2

Previous work regarding low-rank matrix recovery has concentrated on the scenarios in which the matrix is noise-free and the measurements are corrupted by noise. However, in practi…