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15 October 2012 Phase-space analysis of sparse signals and compressive sensing
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Abstract
Compressive sampling schemes for sparse signals are investigated in the framework of phase-space optics. Phasespace representations are used to identify signal sparsity and construct compressive sensing schemes. Both linear and nonlinear compressive sampling methods are interpreted as applications of Lukosz superresolution. For two iterative methods, the l1-magic algorithm and the CLEAN algorithm, numerical experiments are performed to determine the practical limits of sparse signal recovery. In addition, the phase-space interpretation is used to construct a phase retrieval algorithm for signals with a sparse phase space.
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Markus E. Testorf "Phase-space analysis of sparse signals and compressive sensing", Proc. SPIE 8500, Image Reconstruction from Incomplete Data VII, 850004 (15 October 2012); https://doi.org/10.1117/12.929758
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