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On the convergence of general projection methods for solving convex feasibility problems with applications to the inverse problem of image recovery

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Abstract For an arbitrary family of closed convex sets with nonempty intersection in a Hilbert space, we consider the classical convex feasibility problem. We study the convergence property of the… Click to show full abstract

Abstract For an arbitrary family of closed convex sets with nonempty intersection in a Hilbert space, we consider the classical convex feasibility problem. We study the convergence property of the recently introduced unified projection algorithm B-EMOPP for solving this problem. For this, a new general control strategy is proposed, which we call the ‘quasi-coercive control’. Under mild assumptions, we prove the convergence of B-EMOPP using these new control strategies as well as various other strategies. Several known results are extended and improved. The proposed algorithm is then applied to the inverse problem of image recovery.

Keywords: problem image; convex feasibility; image recovery; inverse problem; problem; convergence

Journal Title: Optimization
Year Published: 2018

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