TY - JOUR
T1 - Second order self-adaptive dynamical system for sparse signal reconstruction and applications to image recovery
AU - Che, Haitao
AU - Liu, Kaiping
AU - Chen, Haibin
AU - Yan, Hong
PY - 2023/8/15
Y1 - 2023/8/15
N2 - In this article, we consider sparse signal reconstruction problems by an alternative second order self-adaptive dynamical system. By split feasibility problem of sparse signal reconstruction, we introduce a new second order self-adaptive dynamical system. Then, we prove that the proposed system has a unique solution under reasonable conditions. Furthermore, it is shown that the corresponding orbit of the system always converges. Finally, all kinds of numerical results on synthetic data and data from practical problems verify the efficiency of the proposed approach. © 2023 Elsevier Inc.
AB - In this article, we consider sparse signal reconstruction problems by an alternative second order self-adaptive dynamical system. By split feasibility problem of sparse signal reconstruction, we introduce a new second order self-adaptive dynamical system. Then, we prove that the proposed system has a unique solution under reasonable conditions. Furthermore, it is shown that the corresponding orbit of the system always converges. Finally, all kinds of numerical results on synthetic data and data from practical problems verify the efficiency of the proposed approach. © 2023 Elsevier Inc.
KW - CQ algorithm
KW - Dynamical system
KW - Self-adaptive
KW - Split feasibility problem
UR - http://www.scopus.com/inward/record.url?scp=85152598859&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85152598859&origin=recordpage
U2 - 10.1016/j.amc.2023.128019
DO - 10.1016/j.amc.2023.128019
M3 - RGC 21 - Publication in refereed journal
SN - 0096-3003
VL - 451
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
M1 - 128019
ER -