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 - <p style="text-align: justify;">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.</p>