Proximal Splitting Methods in Signal Processing

Abstract : The proximity operator of a convex function is a natural extension of the notion of a projection operator onto a convex set. This tool, which plays a central role in the analysis and the numerical solution of convex optimization problems, has recently been introduced in the arena of signal processing, where it has become increasingly important. In this paper, we review the basic properties of proximity operators which are relevant to signal processing and present optimization methods based on these operators. These proximal splitting methods are shown to capture and extend several well-known algorithms in a unifying framework. Applications of proximal methods in signal recovery and synthesis are discussed.
keyword : sadco
Type de document :
Chapitre d'ouvrage
Bauschke, H.H.; Burachik, R.S.; Combettes, P.L.; Elser, V.; Luke, D.R.; Wolkowicz, H. (Eds.). Fixed-Point Algorithms for Inverse Problems in Science and Engineering, Springer, pp.185-212, 2011, 978-1-4419-9568-1. <10.1007/978-1-4419-9569-8>


https://hal.inria.fr/hal-00643807
Contributeur : Estelle Bouzat <>
Soumis le : mardi 22 novembre 2011 - 18:45:37
Dernière modification le : mercredi 12 octobre 2016 - 01:20:38

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Patrick Louis Combettes, Jean-Christophe Pesquet. Proximal Splitting Methods in Signal Processing. Bauschke, H.H.; Burachik, R.S.; Combettes, P.L.; Elser, V.; Luke, D.R.; Wolkowicz, H. (Eds.). Fixed-Point Algorithms for Inverse Problems in Science and Engineering, Springer, pp.185-212, 2011, 978-1-4419-9568-1. <10.1007/978-1-4419-9569-8>. <hal-00643807>

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