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

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  • Suthep Suantai

    (Research Group in Mathematics and Applied Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
    Data Science Research Center, Department of 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)

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.

Suggested Citation

  • Suthep Suantai & Kunrada Kankam & Watcharaporn Cholamjiak & Watcharaporn Yajai, 2022. "Parallel Hybrid Algorithms for a Finite Family of G -Nonexpansive Mappings and Its Application in a Novel Signal Recovery," Mathematics, MDPI, vol. 10(12), pages 1-16, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2140-:d:842847
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    Cited by:

    1. Suthep Suantai & Kunrada Kankam & Damrongsak Yambangwai & Watcharaporn Cholamjiak, 2022. "A Modified Inertial Parallel Viscosity-Type Algorithm for a Finite Family of Nonexpansive Mappings and Its Applications," Mathematics, MDPI, vol. 10(23), pages 1-21, November.

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