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Fast Iterative Shrinkage for Signal Declipping and Dequantization

Rencker, Lucas, Bach, Francis, Wang, Wenwu and Plumbley, Mark D. (2018) Fast Iterative Shrinkage for Signal Declipping and Dequantization In: iTWIST’18 - International Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, 21-23 Nov 2018, CIRM, Marseille, France.

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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.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Rencker, Lucaslucas.rencker@surrey.ac.uk
Bach, Francis
Wang, WenwuW.Wang@surrey.ac.uk
Plumbley, Mark D.m.plumbley@surrey.ac.uk
Date : 21 November 2018
Copyright Disclaimer : © 2018 the author(s)
Related URLs :
Depositing User : Clive Harris
Date Deposited : 19 Sep 2018 10:24
Last Modified : 30 Aug 2019 15:59
URI: http://epubs.surrey.ac.uk/id/eprint/849354

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