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Cited 52 time in webofscience Cited 52 time in scopus
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Inertial relaxed<i>CQ</i>algorithms for solving a split feasibility problem in Hilbert spaces

Authors
Sahu, D. R.Cho, Y. J.Dong, Q. L.Kashyap, M. R.Li, X. H.
Issue Date
Jul-2021
Publisher
SPRINGER
Keywords
Split feasibility problem; CQ algorithm; Inertial technique; Self-adaptive algorithm; Weak convergence
Citation
NUMERICAL ALGORITHMS, v.87, no.3, pp 1075 - 1095
Pages
21
Indexed
SCIE
SCOPUS
Journal Title
NUMERICAL ALGORITHMS
Volume
87
Number
3
Start Page
1075
End Page
1095
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/72416
DOI
10.1007/s11075-020-00999-2
ISSN
1017-1398
1572-9265
Abstract
The split feasibility problem is to find a pointx*with the property thatx*is an element of CandAx*is an element of Q, whereCandQare nonempty closed convex subsets of real Hilbert spacesXandY, respectively, andAis a bounded linear operator fromXtoY. The split feasibility problem models inverse problems arising from phase retrieval problems and the intensity-modulated radiation therapy. In this paper, we introduce a new inertial relaxedCQalgorithm for solving the split feasibility problem in real Hilbert spaces and establish weak convergence of the proposedCQalgorithm under certain mild conditions. Our result is a significant improvement of the recent results related to the split feasibility problem.
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