Geodesic
Efficient projective methods for the split feasibility problem and its applications to compressed sensing and image debluring
Filomat, Tome 35 (2021) no. 10, p. 3241

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DOI

In this paper, new projective algorithms using linesearch technique are proposed to solve the split feasibility problem. Weak convergence theorems are established, under suitable conditions, in a real Hilbert space. Some numerical experiments in compressed sensing and image debluring are also provided to show its implementation and efficiency. The main results improve the corresponding results in the literature
DOI : 10.2298/FIL2110241K
Classification : 47H10, 54H25
Keywords: split feasibility problem, projection algorithm, Hilbert space, Weak convergence 
Suparat Kesornprom; Nattawut Pholasa; Prasit Cholamjiak. Efficient projective methods for the split feasibility problem and its applications to compressed sensing and image debluring. Filomat, Tome 35 (2021) no. 10, p. 3241 . doi: 10.2298/FIL2110241K
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     title = {Efficient projective methods for the split feasibility problem and its applications to compressed sensing and image debluring},
     journal = {Filomat},
     pages = {3241 },
     year = {2021},
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     doi = {10.2298/FIL2110241K},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2110241K/}
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