full
search.png

Search

close.png

Cancel

arrow
Volume 42, Issue 1
Stable Recovery of Sparsely Corrupted Signals Through Justice Pursuit De-Noising

Ningning Li, Wengu Chen & Huanmin Ge

DOI: 10.4208/jcm.2204-m2021-0333

J. Comp. Math., 42 (2024), pp. 271-288.

Published online: 2023-12

Preview Full PDF 1347 20022

Cited by

google scholar semantic scholar
Export citation
  • Abstract

This paper considers a corrupted compressed sensing problem and is devoted to recover signals that are approximately sparse in some general dictionary but corrupted by a combination of interference having a sparse representation in a second general dictionary and measurement noise. We provide new restricted isometry property (RIP) analysis to achieve stable recovery of sparsely corrupted signals through Justice Pursuit De-Noising (JPDN) with an additional parameter. Our main tool is to adapt a crucial sparse decomposition technique to the analysis of the Justice Pursuit method. The proposed RIP condition improves the existing representative results. Numerical simulations are provided to verify the reliability of the JPDN model.

  • Keywords

Justice Pursuit De-Noising, Restricted isometry property, Corrupted compressed sensing, Signal recovery.

  • AMS Subject Headings

65F22, 68W25, 90C25

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JCM-42-271, author = {Li , NingningChen , Wengu and Ge , Huanmin}, title = {Stable Recovery of Sparsely Corrupted Signals Through Justice Pursuit De-Noising}, journal = {Journal of Computational Mathematics}, year = {2023}, volume = {42}, number = {1}, pages = {271--288}, abstract = {

This paper considers a corrupted compressed sensing problem and is devoted to recover signals that are approximately sparse in some general dictionary but corrupted by a combination of interference having a sparse representation in a second general dictionary and measurement noise. We provide new restricted isometry property (RIP) analysis to achieve stable recovery of sparsely corrupted signals through Justice Pursuit De-Noising (JPDN) with an additional parameter. Our main tool is to adapt a crucial sparse decomposition technique to the analysis of the Justice Pursuit method. The proposed RIP condition improves the existing representative results. Numerical simulations are provided to verify the reliability of the JPDN model.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.2204-m2021-0333}, url = {http://global-sci.org/intro/article_detail/jcm/22160.html} }
TY - JOUR T1 - Stable Recovery of Sparsely Corrupted Signals Through Justice Pursuit De-Noising AU - Li , Ningning AU - Chen , Wengu AU - Ge , Huanmin JO - Journal of Computational Mathematics VL - 1 SP - 271 EP - 288 PY - 2023 DA - 2023/12 SN - 42 DO - http://doi.org/10.4208/jcm.2204-m2021-0333 UR - https://global-sci.org/intro/article_detail/jcm/22160.html KW - Justice Pursuit De-Noising, Restricted isometry property, Corrupted compressed sensing, Signal recovery. AB -

This paper considers a corrupted compressed sensing problem and is devoted to recover signals that are approximately sparse in some general dictionary but corrupted by a combination of interference having a sparse representation in a second general dictionary and measurement noise. We provide new restricted isometry property (RIP) analysis to achieve stable recovery of sparsely corrupted signals through Justice Pursuit De-Noising (JPDN) with an additional parameter. Our main tool is to adapt a crucial sparse decomposition technique to the analysis of the Justice Pursuit method. The proposed RIP condition improves the existing representative results. Numerical simulations are provided to verify the reliability of the JPDN model.

Li , NingningChen , Wengu and Ge , Huanmin. (2023). Stable Recovery of Sparsely Corrupted Signals Through Justice Pursuit De-Noising. Journal of Computational Mathematics. 42 (1). 271-288. doi:10.4208/jcm.2204-m2021-0333
Copy to clipboard
BibteX RIS TXT
The citation has been copied to your clipboard