New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces

The split feasibility problem SFP has received much attention due to its various applications in signal processing and image reconstruction. In this paper, we propose two inertial relaxed CQ algorithms for solving the split feasibility problem in real Hilbert spaces according to the previous experie...

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Main Authors: Haiying Li, Yulian Wu, Fenghui Wang
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2021/6624509
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author Haiying Li
Yulian Wu
Fenghui Wang
author_facet Haiying Li
Yulian Wu
Fenghui Wang
author_sort Haiying Li
collection DOAJ
description The split feasibility problem SFP has received much attention due to its various applications in signal processing and image reconstruction. In this paper, we propose two inertial relaxed CQ algorithms for solving the split feasibility problem in real Hilbert spaces according to the previous experience of applying inertial technology to the algorithm. These algorithms involve metric projections onto half-spaces, and we construct new variable step size, which has an exact form and does not need to know a prior information norm of bounded linear operators. Furthermore, we also establish weak and strong convergence of the proposed algorithms under certain mild conditions and present a numerical experiment to illustrate the performance of the proposed algorithms.
format Article
id doaj-art-8530d33296944f61aad7b74954cce3df
institution OA Journals
issn 2314-4629
2314-4785
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Journal of Mathematics
spelling doaj-art-8530d33296944f61aad7b74954cce3df2025-08-20T02:08:57ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/66245096624509New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert SpacesHaiying Li0Yulian Wu1Fenghui Wang2College of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, ChinaCollege of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, ChinaDepartment of Mathematics, Luoyang Normal University, Luoyang 471934, ChinaThe split feasibility problem SFP has received much attention due to its various applications in signal processing and image reconstruction. In this paper, we propose two inertial relaxed CQ algorithms for solving the split feasibility problem in real Hilbert spaces according to the previous experience of applying inertial technology to the algorithm. These algorithms involve metric projections onto half-spaces, and we construct new variable step size, which has an exact form and does not need to know a prior information norm of bounded linear operators. Furthermore, we also establish weak and strong convergence of the proposed algorithms under certain mild conditions and present a numerical experiment to illustrate the performance of the proposed algorithms.http://dx.doi.org/10.1155/2021/6624509
spellingShingle Haiying Li
Yulian Wu
Fenghui Wang
New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
Journal of Mathematics
title New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
title_full New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
title_fullStr New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
title_full_unstemmed New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
title_short New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces
title_sort new inertial relaxed cq algorithms for solving split feasibility problems in hilbert spaces
url http://dx.doi.org/10.1155/2021/6624509
work_keys_str_mv AT haiyingli newinertialrelaxedcqalgorithmsforsolvingsplitfeasibilityproblemsinhilbertspaces
AT yulianwu newinertialrelaxedcqalgorithmsforsolvingsplitfeasibilityproblemsinhilbertspaces
AT fenghuiwang newinertialrelaxedcqalgorithmsforsolvingsplitfeasibilityproblemsinhilbertspaces