A contraction proximal point algorithm with two monotone operators

Oganeditse A. Boikanyo, Gheorghe Moroşanu

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


It is a known fact that the method of alternating projections introduced long ago by von Neumann fails to converge strongly for two arbitrary nonempty, closed and convex subsets of a real Hilbert space. In this paper, a new iterative process for finding common zeros of two maximal monotone operators is introduced and strong convergence results associated with it are proved. If the two operators are subdifferentials of indicator functions, this new algorithm coincides with the old method of alternating projections. Several other important algorithms, such as the contraction proximal point algorithm, occur as special cases of our algorithm. Hence our main results generalize and unify many results that occur in the literature.

Original languageEnglish
Pages (from-to)5686-5692
Number of pages7
JournalNonlinear Analysis, Theory, Methods and Applications
Issue number14
Publication statusPublished - Sept 2012

All Science Journal Classification (ASJC) codes

  • Analysis
  • Applied Mathematics


Dive into the research topics of 'A contraction proximal point algorithm with two monotone operators'. Together they form a unique fingerprint.

Cite this