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A block-iterative quadratic signal recovery algorithm

We propose a block-iterative parallel decomposition method to solve quadratic signal recovery problems under convex constraints. The idea, of the method is to disintegrate the original multi-constraint problem into a sequence of simple quadratic minimizations over the intersection of two half-spaces constructed by linearizing blocks of constraints. The implementation of the algorithm is quite flexible thanks to its block-parallel structure. In addition a wide range of complex constraints can be incorporated since the method does not require exact constraint enforcement at each step but merely approximate enforcement via linearization. An application to deconvolution is demonstrated.