A proximal point algorithm converging strongly for general errors

TitleA proximal point algorithm converging strongly for general errors
Publication TypeJournal Article
AuthorsBoikanyo, Oganeditse A., and Gheorghe Morosanu
Journal titleOptimization Letters
Year2010
Pages635–641
Volume4
Abstract

In this paper a proximal point algorithm (PPA) for maximal monotone operators with appropriate regularization parameters is considered. A strong convergence result for PPA is stated and proved under the general condition that the error sequence tends to zero in norm. Note that Rockafellar (SIAM J Control Optim 14:877–898, 1976) assumed summability for the error sequence to derive weak convergence of PPA in its initial form, and this restrictive condition on errors has been extensively used sofar for different versions of PPA. Thus this Note provides a lutiontoalongstandingopenproblemandinparticularoffersnewpossibilitiestowards
the approximation of the minimum points of convex functionals.

LanguageEnglish
DOI10.1007/s11590-010-0176-z
Publisher linkhttp://www.springerlink.com/content/2525h8w257268264/
Unit: 
Department of Mathematics and its Applications
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