Abstract
The split feasibility problem is an inverse problem which arises in signal processing and medical image reconstruction. So there is practical value in studying it. While both the split equality problem and the split variational inclusion problem are generalized form of the split feasibility problem which are more meaningful than the split feasibility problem. In this paper, fusing the two problems, we research a split inclusion problem and propose relevant methods for solving it. What counts is that not only the proposed algorithms have strong convergence, but also the limit points of the algorithms are the minimal norm solution of the split inclusion problem.
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This research was supported by NSFC Grants Nos.: 11226125 and 11301379. Author’s contributions All authors contributed equally and significantly in writing this paper. All authors read and approved the final manuscript.
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Tian, D., Shi, L. & Chen, R. Strong convergence theorems for split inclusion problems in Hilbert spaces. J. Fixed Point Theory Appl. 19, 1501–1514 (2017). https://doi.org/10.1007/s11784-017-0422-4
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DOI: https://doi.org/10.1007/s11784-017-0422-4