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Open AccessArticle

Three-Step Projective Methods for Solving the Split Feasibility Problems

1
Data Science Research Center, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
2
Demonstration School, University of Phayao, Phayao 56000, Thailand
3
School of Science, University of Phayao, Phayao 56000, Thailand
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(8), 712; https://doi.org/10.3390/math7080712
Received: 30 June 2019 / Revised: 22 July 2019 / Accepted: 31 July 2019 / Published: 6 August 2019
(This article belongs to the Special Issue Fixed Point, Optimization, and Applications)
In this paper, we focus on studying the split feasibility problem (SFP) in Hilbert spaces. Based on the CQ algorithm involving the self-adaptive technique, we introduce a three-step iteration process for approximating the solution of SFP. Then, the convergence results are established under mild conditions. Numerical experiments are provided to show the efficiency in signal processing. Some comparisons to various methods are also provided in this paper. View Full-Text
Keywords: self-adaptive technique; split feasibility problem; convergence theorems; Hilbert space; CQ algorithm self-adaptive technique; split feasibility problem; convergence theorems; Hilbert space; CQ algorithm
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Suantai, S.; Eiamniran, N.; Pholasa, N.; Cholamjiak, P. Three-Step Projective Methods for Solving the Split Feasibility Problems. Mathematics 2019, 7, 712.

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