Parallel Hybrid Algorithms for a Finite Family of G -Nonexpansive Mappings and Its Application in a Novel Signal Recovery

Suthep Suantai, Kunrada Kankam, Watcharaporn Cholamjiak and Watcharaporn Yajai
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Suthep Suantai: Research Group in Mathematics and Applied Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
Kunrada Kankam: School of Science, University of Phayao, Phayao 56000, Thailand
Watcharaporn Cholamjiak: School of Science, University of Phayao, Phayao 56000, Thailand
Watcharaporn Yajai: School of Science, University of Phayao, Phayao 56000, Thailand

Mathematics, 2022, vol. 10, issue 12, 1-16

Abstract: This article considers a parallel monotone hybrid algorithm for a finite family of G -nonexpansive mapping in Hilbert spaces endowed with graphs and suggests iterative schemes for finding a common fixed point by the two different hybrid projection methods. Moreover, we show the computational performance of our algorithm in comparison to some methods. Strong convergence theorems are proved under suitable conditions. Finally, we give some numerical experiments of our algorithms to show the efficiency and implementation of the LASSO problems in signal recovery with different types of blurred matrices and noise.

Keywords: hybrid projection method; parallel hybrid method; G -nonexpansive mapping; signal recovery (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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