Multi parameter proximal point algorithms

Oganeditse A. Boikanyo, Gheorghe Moroşanu

    Research output: Contribution to journalArticle

    3 Citations (Scopus)

    Abstract

    The aim of this paper is to prove a strong convergence result for an algorithm introduced by Y. Yao and M. A. Noor in 2008 under a new condition on one of the parameters involved. Further, convergence properties of a generalized proximal point algorithm which was introduced in [5] axe analyzed. The results in this paper axe proved under the general condition that errors tend to zero in norm. These results extend and improve several previous results on the regularization method and the proximal point algorithm.

    Original languageEnglish
    Pages (from-to)221-231
    Number of pages11
    JournalJournal of Nonlinear and Convex Analysis
    Volume13
    Issue number2
    Publication statusPublished - May 2012

    Fingerprint

    Proximal Point Algorithm
    Regularization Method
    Strong Convergence
    Convergence Properties
    Convergence Results
    Tend
    Norm
    Zero

    All Science Journal Classification (ASJC) codes

    • Analysis
    • Applied Mathematics
    • Control and Optimization
    • Geometry and Topology

    Cite this

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    Multi parameter proximal point algorithms. / Boikanyo, Oganeditse A.; Moroşanu, Gheorghe.

    In: Journal of Nonlinear and Convex Analysis, Vol. 13, No. 2, 05.2012, p. 221-231.

    Research output: Contribution to journalArticle

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