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dc.contributor.authorRaweerote Suparatulatornen_US
dc.contributor.authorPhakdi Charoensawanen_US
dc.contributor.authorKanyuta Poochinapanen_US
dc.date.accessioned2019-09-16T12:52:34Z-
dc.date.available2019-09-16T12:52:34Z-
dc.date.issued2019-01-01en_US
dc.identifier.issn10991476en_US
dc.identifier.issn01704214en_US
dc.identifier.other2-s2.0-85070921493en_US
dc.identifier.other10.1002/mma.5836en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070921493&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/66666-
dc.description.abstract© 2019 John Wiley & Sons, Ltd. We introduce a new self-adaptive algorithm for applications to image restoration problems. In order to study an image restoration, we consider the algorithm that contains inertial effects and step sizes, which is independent from the norm of the bounded linear operator. With some control conditions, the strong convergence to the minimum norm solution of the algorithm is obtained. Convergence analysis of the proposed algorithm is also discussed. Moreover, numerical results of image restoration problems illustrate that the proposed algorithm is efficient and outperforms other ones.en_US
dc.subjectEngineeringen_US
dc.subjectMathematicsen_US
dc.titleInertial self-adaptive algorithm for solving split feasible problems with applications to image restorationen_US
dc.typeJournalen_US
article.title.sourcetitleMathematical Methods in the Applied Sciencesen_US
article.stream.affiliationsSouth Carolina Commission on Higher Educationen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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