151 citations · 168 across the 12 of their papers we have counts for
13 papers
Guaranteed Tensor Recovery Fused Low-rankness and Smoothness
Hailin Wang, Jiangjun Peng, Wenjin Qin +2
The tensor data recovery task has thus attracted much research attention in recent years. Solving such an ill-posed problem generally requires to explore intrinsic prior structures…
Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices
Jiangjun Peng, Yao Wang, Hongying Zhang +2
It is known that the decomposition in low-rank and sparse matrices (\textbf{L+S} for short) can be achieved by several Robust PCA techniques. Besides the low rankness, the local sm…
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…
The block mutual coherence property condition for signal recovery
Jianwen Huang, Hailin Wang, Feng Zhang +2
Compressed sensing shows that a sparse signal can stably be recovered from incomplete linear measurements. But, in practical applications, some signals have additional structure, w…
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…
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…