Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem

The split feasibility problem models inverse problems arising from phase retrievals problems and intensity-modulated radiation therapy. For solving the split feasibility problem, Xu proposed a relaxed CQ algorithm that only involves projections onto half-spaces. In this paper, we use the dual variab...

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Main Authors: Xinglong Wang, Jing Zhao, Dingfang Hou
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/7/2/119
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author Xinglong Wang
Jing Zhao
Dingfang Hou
author_facet Xinglong Wang
Jing Zhao
Dingfang Hou
author_sort Xinglong Wang
collection DOAJ
description The split feasibility problem models inverse problems arising from phase retrievals problems and intensity-modulated radiation therapy. For solving the split feasibility problem, Xu proposed a relaxed CQ algorithm that only involves projections onto half-spaces. In this paper, we use the dual variable to propose a new relaxed CQ iterative algorithm that generalizes Xu’s relaxed CQ algorithm in real Hilbert spaces. By using projections onto half-spaces instead of those onto closed convex sets, the proposed algorithm is implementable. Moreover, we present modified relaxed CQ algorithm with viscosity approximation method. Under suitable conditions, global weak and strong convergence of the proposed algorithms are proved. Some numerical experiments are also presented to illustrate the effectiveness of the proposed algorithms. Our results improve and extend the corresponding results of Xu and some others.
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spelling doaj.art-ac4b9ba2b6f64ed7b5cf5b05bf59a1a72022-12-21T18:19:26ZengMDPI AGMathematics2227-73902019-01-017211910.3390/math7020119math7020119Modified Relaxed CQ Iterative Algorithms for the Split Feasibility ProblemXinglong Wang0Jing Zhao1Dingfang Hou2College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, ChinaCollege of Science, Civil Aviation University of China, Tianjin 300300, ChinaCollege of Science, Civil Aviation University of China, Tianjin 300300, ChinaThe split feasibility problem models inverse problems arising from phase retrievals problems and intensity-modulated radiation therapy. For solving the split feasibility problem, Xu proposed a relaxed CQ algorithm that only involves projections onto half-spaces. In this paper, we use the dual variable to propose a new relaxed CQ iterative algorithm that generalizes Xu’s relaxed CQ algorithm in real Hilbert spaces. By using projections onto half-spaces instead of those onto closed convex sets, the proposed algorithm is implementable. Moreover, we present modified relaxed CQ algorithm with viscosity approximation method. Under suitable conditions, global weak and strong convergence of the proposed algorithms are proved. Some numerical experiments are also presented to illustrate the effectiveness of the proposed algorithms. Our results improve and extend the corresponding results of Xu and some others.https://www.mdpi.com/2227-7390/7/2/119split feasibility problemrelaxed CQ algorithmconvergenceHilbert space
spellingShingle Xinglong Wang
Jing Zhao
Dingfang Hou
Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
Mathematics
split feasibility problem
relaxed CQ algorithm
convergence
Hilbert space
title Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
title_full Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
title_fullStr Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
title_full_unstemmed Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
title_short Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem
title_sort modified relaxed cq iterative algorithms for the split feasibility problem
topic split feasibility problem
relaxed CQ algorithm
convergence
Hilbert space
url https://www.mdpi.com/2227-7390/7/2/119
work_keys_str_mv AT xinglongwang modifiedrelaxedcqiterativealgorithmsforthesplitfeasibilityproblem
AT jingzhao modifiedrelaxedcqiterativealgorithmsforthesplitfeasibilityproblem
AT dingfanghou modifiedrelaxedcqiterativealgorithmsforthesplitfeasibilityproblem