Abstract

Howard’s minimum-negativity-constraint extrapolation algorithm is shown to be a special case of signal recovery by means of alternating convex set projections. Previously derived results in this richly developed field of analysis [ Appl. Opt. 25, 1670 ( 1986); J. Opt. Soc. Am. 71, 819 ( 1981)] are applied immediately to establish strong convergence for the extrapolation algorithm.

© 1988 Optical Society of America

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