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A Krasnoselskii-Type Algorithm for Approximating Solutions of Variational Inequality Problems and Convex Feasibility Problems

dc.contributor.authorAbubakar, Adamu
dc.date.accessioned2020-01-27T08:31:31Z
dc.date.available2020-01-27T08:31:31Z
dc.date.issued2017-12-18
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/123456789/4940
dc.description.abstractA Krasnoselskii-type algorithm for approximating a common element of the set of solutions of a variational inequality problem for a monotone, k-Lipschitz map and solutions of a convex feasibility problem involving a countable family of relatively nonexpansive maps is studied in a uniformly smooth and 2-uniformly convex real Banach space. A strong convergence theorem is proved. Some applications of the theorem are presented.en_US
dc.description.sponsorshipAUST and AfDB.en_US
dc.language.isoenen_US
dc.subjectAbubakar Adamuen_US
dc.subjectProf. Charles Ejikeme Chidumeen_US
dc.subjectRelatively nonepxansive mapsen_US
dc.subjectmonotone mapsen_US
dc.subjectLipschitz continuous mapsen_US
dc.subjectgen- eralized projectionen_US
dc.subjectvariational inequality problemsen_US
dc.subjectcountable familyen_US
dc.subjectsubgradient methoden_US
dc.titleA Krasnoselskii-Type Algorithm for Approximating Solutions of Variational Inequality Problems and Convex Feasibility Problemsen_US
dc.typeThesisen_US


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