Hilbertian Convex Feasibility Problem: Convergence of Projection Methods∗
نویسنده
چکیده
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 this broad framework, which provides a unified view of projection methods for solving hilbertian convex feasibility problems.
منابع مشابه
Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems
Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems Amir Beck & Marc Teboulle To cite this article: Amir Beck & Marc Teboulle (2003) Convergence rate analysis and error bounds for projection algorithms in convex feasibility problems, Optimization Methods and Software, 18:4, 377-394, DOI: 10.1080/10556780310001604977 To link to this article: http:/...
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تاریخ انتشار 1997