Strong convergence of expected-projection methods in hilbert spaces

DOI10.1080/01630569508816635zbMath0834.65041OpenAlexW2033390858MaRDI QIDQ4845180

Dan Butnariu, Sjur Didrik Flåm

Publication date: 18 October 1995

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630569508816635

zbMATH Keywords

strong convergenceHilbert spacesprojection methodscomputational tomographystochastic convex feasibility problemsbest-approximation problemsstochastic systems of convex inequalities

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) General theory of numerical analysis in abstract spaces (65J05) Stochastic programming (90C15) Biomedical imaging and signal processing (92C55) Best approximation, Chebyshev systems (41A50) Random nonlinear operators (47H40)

Related Items

Stochastic quasi-subgradient method for stochastic quasi-convex feasibility problems, Convergence of Bregman projection methods for solving consistent convex feasibility problems in reflexive Banach spaces, The method of randomized Bregman projections for stochastic feasibility problems, Unnamed Item, Random Function Iterations for Consistent Stochastic Feasibility, Hilbertian convex feasibility problem: Convergence of projection methods, Non-Convex feasibility problems and proximal point methods, Existence and approximation of solutions for Fredholm equations of the first kind with applications to a linear moment problem, A Hierarchical Presentation of Operators with Fixed Points on Hilbert Spaces, Unnamed Item, An estimate for Lipschitz constants of metric projections, Unconstrained Optimization Techniques for the Acceleration of Alternating Projection Methods

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