Three-step projected forwardÐbackward algorithms for constrained minimization problem

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dc.contributor.authorKunrada Kankam
dc.contributor.authorMuhammad Aslam Noor
dc.contributor.authorPrasit Cholamjiak
dc.contributor.correspondenceP. Cholamjiak; School of Science, University of Phayao, Phayao, 56000, Thailand; email: prasitch2008@yahoo.com
dc.date.accessioned2025-03-10T07:22:48Z
dc.date.available2025-03-10T07:22:48Z
dc.date.issued2025
dc.description.abstractWe design new projective forwardÐbackward algorithms for constrained minimization problems. We then discuss its weak convergence via a new linesearch that the hypothesis on the Lipschitz constant of the gradient of functions is avoided. We provide its applications to solve image deblurring and image inpainting. Finally, we discuss the optimal selection of parameters that are proposed in algorithms in terms of PSNR and SSIM. It reveals that our new algorithm outperforms some recent methods introduced in the literature. © The Author(s) under exclusive licence to Korean Society for Informatics and Computational Applied Mathematics 2024.
dc.identifier.citationJournal of Applied Mathematics and Computing
dc.identifier.doi10.1007/s12190-024-02248-4
dc.identifier.issn15985865
dc.identifier.scopus2-s2.0-85205080788
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/4437
dc.languageEnglish
dc.publisherSpringer Nature
dc.rights.holderScopus
dc.subjectForwardÐbackward algorithm
dc.subjectLinesearch method
dc.subjectMinimization problem
dc.subjectWeak convergence
dc.titleThree-step projected forwardÐbackward algorithms for constrained minimization problem
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205080788&doi=10.1007%2fs12190-024-02248-4&partnerID=40&md5=37b794c4ef8b1ed0aafa75926660ff49
oaire.citation.endPage487
oaire.citation.issue1
oaire.citation.startPage465
oaire.citation.volume71
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