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Applied Mathematics and Optimization

, Volume 35, Issue 3, pp 311–330 | Cite as

Hilbertian convex feasibility problem: Convergence of projection methods

  • P. L. Combettes
Article

Abstract

The classical problem of finding a point in the intersection of countably many closed and convex sets in a Hilbert space is considered. Extrapolated iterations of convex combinations of approximate projections onto subfamilies of sets are investigated to solve this problem. General hypotheses are made on the regularity of the sets and various strategies are considered to control the order in which the sets are selected. Weak and strong convergence results are established within thisbroad framework, which provides a unified view of projection methods for solving hilbertian convex feasibility problems.

Key Words

Alternating projections Boundedly regular sets Chaotic iterations Convergence Convex feasibility problem Convex sets Extrapolated projections Fejér-monotone sequences Hilbert spaces Parallel projections Relaxations Successive projections 

AMS Classification

90C25 65J05 52A41 40A05 

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Copyright information

© Springer-Verlag New York Inc 1997

Authors and Affiliations

  • P. L. Combettes
    • 1
  1. 1.Department of Electrical Engineering, City College and Graduate SchoolCity University of New YorkNew YorkUSA

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