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Proximal splitting methods in signal processing. (English) Zbl 1242.90160
Bauschke, Heinz H. (ed.) et al., Fixed-point algorithms for inverse problems in science and engineering. Based on the presentations at the interdisciplinary workshop, BIRS, Banff, Canada, November 1–6, 2009. New York, NY: Springer (ISBN 978-1-4419-9568-1/hbk; 978-1-4419-9569-8/ebook). Springer Optimization and Its Applications 49, 185-212 (2011).
Summary: 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 inverse problems and, especially, in 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.
For the entire collection see [Zbl 1217.00018].

MSC:
90C25 Convex programming
65K05 Numerical mathematical programming methods
90C90 Applications of mathematical programming
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
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