The effect of perturbation and noise folding on the recovery performance of low-rank matrix via the nuclear norm minimization

The effect of perturbation and noise folding on the recovery performance of low-rank matrix via the nuclear norm minimization

Previous works in low-rank matrix recovery literature focused on the study of the partially perturbed low-rank matrix recovery model y=A(X)+ω, where y∈RM is the observed vector, A:Rm×n→RM is the measurement operator, X∈Rm×n is the matrix to be recovered, and ω∈RM is the additive noise. However in pr...

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Bibliographic Details
Main Authors: Zahia Aidene, Jianwen Huang, Jianjun Wang
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Intelligent Systems with Applications
Subjects:
Low-rank matrix recovery
Noise folding
Multiplicative noise
Restricted isometry property
Frobenius-robust rank null space property
Nuclear norm minimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305321000478

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http://www.sciencedirect.com/science/article/pii/S2667305321000478

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