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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