Feng Zhang

Orcid: 0000-0003-1000-8877

Affiliations:
  • Southwest University, School of Mathematics and Statistics, Chongqing, China


According to our database1, Feng Zhang authored at least 40 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Book  In proceedings  Article  PhD thesis  Dataset  Other 

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Online presence:

On csauthors.net:

Bibliography

2026
An Improved Sufficient Condition for Weighted $\ell _{r}-\ell _{1}$ Minimization.
IEEE Signal Process. Lett., 2026

2025
Hyperspectral Anomaly Detection Fused Unified Nonconvex Tensor Ring Factors Regularization.
IEEE Trans. Geosci. Remote. Sens., 2025

Performance analysis of unconstrained ℓp minimization for sparse recovery.
Signal Process., 2025

2024
The Perturbation Analysis of Nonconvex Low-Rank Matrix Robust Recovery.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Enhanced Low-Rank Tensor Recovery Fusing Reweighted Tensor Correlated Total Variation Regularization for Image Denoising.
J. Sci. Comput., June, 2024

Low-tubal-rank tensor completion via local and nonlocal knowledge.
Inf. Sci., February, 2024

Nonconvex Robust High-Order Tensor Completion Using Randomized Low-Rank Approximation.
IEEE Trans. Image Process., 2024

Tensor Ring Decomposition-Based Generalized and Efficient Nonconvex Approach for Hyperspectral Anomaly Detection.
IEEE Trans. Geosci. Remote. Sens., 2024

Tensor completion via joint reweighted tensor Q-nuclear norm for visual data recovery.
Signal Process., 2024

2023
Generalized nonconvex regularization for tensor RPCA and its applications in visual inpainting.
Appl. Intell., October, 2023

Low-Tubal-Rank tensor recovery with multilayer subspace prior learning.
Pattern Recognit., August, 2023

Randomized sampling techniques based low-tubal-rank plus sparse tensor recovery.
Knowl. Based Syst., 2023

Signal recovery adapted to a dictionary from non-convex compressed sensing.
Int. J. Comput. Sci. Math., 2023

High-Order Tensor Recovery Coupling Multilayer Subspace Priori with Application in Video Restoration.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

2022
Generalized Nonconvex Approach for Low-Tubal-Rank Tensor Recovery.
IEEE Trans. Neural Networks Learn. Syst., 2022

Low-Rank High-Order Tensor Completion With Applications in Visual Data.
IEEE Trans. Image Process., 2022

A New Sufficient Condition for Non-Convex Sparse Recovery via Weighted $\ell _{r}\!-\!\ell _{1}$ Minimization.
IEEE Signal Process. Lett., 2022

Robust Low-Tubal-Rank Tensor Recovery From Binary Measurements.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021
Low-Tubal-Rank Plus Sparse Tensor Recovery With Prior Subspace Information.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Robust low-rank tensor reconstruction using high-order t-SVD.
J. Electronic Imaging, 2021

Perturbation analysis of low-rank matrix stable recovery.
Int. J. Wavelets Multiresolution Inf. Process., 2021

An optimal condition of robust low-rank matrices recovery.
Int. J. Wirel. Mob. Comput., 2021

Tensor restricted isometry property analysis for a large class of random measurement ensembles.
Sci. China Inf. Sci., 2021

2020
Uniqueness Guarantee of Solutions of Tensor Tubal-Rank Minimization Problem.
IEEE Signal Process. Lett., 2020

RIP-based performance guarantee for low-tubal-rank tensor recovery.
J. Comput. Appl. Math., 2020

Robust principal component analysis with intra-block correlation.
Neurocomputing, 2020

The perturbation analysis of nonconvex low-rank matrix robust recovery.
CoRR, 2020

An Optimal Condition of Robust Low-rank Matrices Recovery.
CoRR, 2020

An analysis of noise folding for low-rank matrix recovery.
CoRR, 2020

Estimating Structural Missing Values Via Low-Tubal-Rank Tensor Completion.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Low-Tubal-Rank Tensor Recovery From One-Bit Measurements.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A nonconvex penalty function with integral convolution approximation for compressed sensing.
Signal Process., 2019

Image denoising in impulsive noise via weighted Schatten p -norm regularization.
J. Electronic Imaging, 2019

Sharp sufficient condition of block signal recovery via <i>l</i> <sub>2</sub>/<i>l</i> <sub>1</sub>-minimisation.
IET Signal Process., 2019

Block-sparse signal recovery based on truncated ℓ 1 minimisation in non-Gaussian noise.
IET Commun., 2019

Coherence-Based Robust Analysis of Basis Pursuit De-Noising and Beyond.
IEEE Access, 2019

2018
Reconstruction analysis of block-sparse signal via truncated ℓ 2 / ℓ 1 -minimisation with redundant dictionaries.
IET Signal Process., 2018

Coherence-Based Performance Guarantee of Regularized 𝓁<sub>1</sub>-Norm Minimization and Beyond.
CoRR, 2018

Perturbations of Compressed Data Separation With Redundant Tight Frames.
IEEE Access, 2018

New Sufficient Conditions of Signal Recovery With Tight Frames via l<sub>1</sub>-Analysis Approach.
IEEE Access, 2018


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