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dc.contributor.authorNipa Jun-Onen_US
dc.contributor.authorRaweerote Suparatulatornen_US
dc.contributor.authorMohamed Gamalen_US
dc.contributor.authorWatcharaporn Cholamjiaken_US
dc.date.accessioned2022-05-27T08:35:12Z-
dc.date.available2022-05-27T08:35:12Z-
dc.date.issued2022-01-01en_US
dc.identifier.issn24736988en_US
dc.identifier.other2-s2.0-85118279366en_US
dc.identifier.other10.3934/math.2022102en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118279366&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/73069-
dc.description.abstractThis study investigates the weak convergence of the sequences generated by the inertial technique combining the parallel monotone hybrid method for finding a common fixed point of a finite family of G-nonexpansive mappings under suitable conditions in Hilbert spaces endowed with graphs. Some numerical examples are also presented, providing applications to signal recovery under situations without knowing the type of noises. Besides, numerical experiments of the proposed algorithms, defined by different types of blurred matrices and noises on the algorithm, are able to show the efficiency and the implementation for LASSO problem in signal recovery.en_US
dc.subjectMathematicsen_US
dc.titleAn inertial parallel algorithm for a finite family of g-nonexpansive mappings applied to signal recoveryen_US
dc.typeJournalen_US
article.title.sourcetitleAIMS Mathematicsen_US
article.volume7en_US
article.stream.affiliationsLampang Rajabhat Universityen_US
article.stream.affiliationsUniversity of Phayaoen_US
article.stream.affiliationsSouth Valley University, Faculty of Scienceen_US
article.stream.affiliationsBeijing Institute of Technologyen_US
article.stream.affiliationsChiang Mai Universityen_US
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