Convergence of String-Averaging Projection Schemes for Inconsistent Convex Feasibility Problems

We study iterative projection algorithms for the convex feasibility problem of finding a point in the intersection of finitely many nonempty, closed and convex subsets in the Euclidean space. We propose (without proof) an algorithmic scheme which genenralizes both the string-averaging algorithm and the block-iterative projections (BIP) method with fixed blocks and prove convergence of the string-averaging method in the inconsistent case by translating it into a fully sequential algorithm in the product space.

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