A modified inertial projected forward–backward algorithm for convex optimization problems

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dc.contributor.authorKunrada Kankam
dc.contributor.authorPapatsara Inkrong
dc.contributor.authorPrasit Cholamjiak
dc.contributor.correspondenceP. Cholamjiak; School of Science, University of Phayao, Phayao, 56000, Thailand; email: prasit.ch@up.ac.th
dc.date.accessioned2025-07-07T18:16:38Z
dc.date.available2025-07-07T18:16:38Z
dc.date.issued2025
dc.description.abstractThe primary objective of this study is to establish the convergence theorem associated with the modified inertial projected forward–backward algorithm using line search techniques. Many applications in applied sciences can be modeled as constrained convex minimization problems. Our numerical experiments offer practical applications for resolving image deblurring issues. The results of our numerical analysis conclusively indicate that the proposed algorithms exhibit greater efficiency than those previously introduced in the literature. © The Author(s), under exclusive licence to Springer-Verlag Italia S.r.l., part of Springer Nature 2024.
dc.identifier.citationRendiconti del Circolo Matematico di Palermo
dc.identifier.doi10.1007/s12215-024-01134-z
dc.identifier.issn0009725X
dc.identifier.scopus2-s2.0-86000199199
dc.identifier.urihttps://repository.dusit.ac.th/handle/123456789/7318
dc.languageEnglish
dc.publisherSpringer-Verlag Italia s.r.l.
dc.rights.holderScopus
dc.subjectConstrained convex minimization problem
dc.subjectImage recovery
dc.subjectProjected forward–backward method
dc.titleA modified inertial projected forward–backward algorithm for convex optimization problems
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-86000199199&doi=10.1007%2fs12215-024-01134-z&partnerID=40&md5=6051c1c68d3a3c38afc8d2d8764248b6
oaire.citation.issue1
oaire.citation.volume74
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