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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