Open AccessEfficient projective methods for the split feasibility problem and its applications to compressed sensing and image debluring
Author(s) -
Suparat Kesornprom,
Nattawut Pholasa,
Prasit Cholamjiak
Publication year - 2021
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil2110241k
Subject(s) - compressed sensing , mathematics , projective test , hilbert space , image (mathematics) , convergence (economics) , mathematical optimization , algorithm , computer vision , computer science , pure mathematics , economics , economic growth
In this paper, new projective algorithms using linesearch technique are proposed to solve the split feasibility problem. Weak convergence theorems are established, under suitable conditions, in a real Hilbert space. Some numerical experiments in compressed sensing and image debluring are also provided to show its implementation and efficiency. The main results improve the corresponding results in the literature.