Strong Convergence of Expected-Projection Methods in Hilbert Spaces

Dan Butnariu, Sjur Didrik Flam

Research output: Contribution to journalArticlepeer-review


Projection methods are iterative algorithms for computing common points of convex sets. They proceed via successive or simultaneous projections onto the given sets. Expected-projection methods, as defined in this work, generalize the simultaneous projection methods. We prove under quite mild conditions, that expected-projection methods in Hilbert spaces converge strongly to almost common points of infinite families of convex sets provided that such points exist. Relying on this result we show how expected-projection methods can be used to solve significant problems of applied mathematics.

Original languageEnglish
Pages (from-to)601-636
Number of pages36
JournalNumerical Functional Analysis and Optimization
Issue number5-6
StatePublished - 1995

ASJC Scopus subject areas

  • Analysis
  • Signal Processing
  • Computer Science Applications
  • Control and Optimization


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