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Fast Iterative Shrinkage for Signal Declipping and Dequantization (1812.01540v1)
Published 4 Dec 2018 in eess.SP
Abstract: We address the problem of recovering a sparse signal from clipped or quantized measurements. We show how these two problems can be formulated as minimizing the distance to a convex feasibility set, which provides a convex and differentiable cost function. We then propose a fast iterative shrinkage/thresholding algorithm that minimizes the proposed cost, which provides a fast and efficient algorithm to recover sparse signals from clipped and quantized measurements.
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