A gradient projection method for the sparse signal reconstruction in compressive sensing. Issue 12 (10th September 2018)

• Record Type: Journal Article
• Authors: Liu, J. K.; Du, X. L.
• Is Part Of: Applicable analysis. Volume 97:Issue 12(2018)
• Page Start: 2122
• Page End: 2131
• Publication Date: 2018-09-10
• Subjects: Compressive sensing -- nonlinear equations -- conjugate gradient method -- projection method -- global convergence; 90C30 -- 65K05; Mathematical analysis -- Periodicals; 515
• DOI: 10.1080/00036811.2017.1359556
• Languages: English
• ISSNs: 0003-6811

Abstract

Abstract: Many problems arising from machine learning, compressive sensing, linear inverse problem, and statistical inference involve finding sparse solutions to under-determined or ill-conditioned equations. In this paper, a gradient projection method is proposed to recover sparse signal in compressive sensing by solving the nonlinear convex constrained equations. The global convergence is established with the backtracking line search. Preliminary numerical experiments coping with the sparse signal reconstruction in compressive sensing are performed, which show that the proposed method is very effective and stable.