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Convex Variational Formulation with Smooth Coupling for Multicomponent Signal Decomposition and Recovery

Convex Variational Formulation with Smooth Coupling for Multicomponent Signal Decomposition and Recovery
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Year:    2009

Numerical Mathematics: Theory, Methods and Applications, Vol. 2 (2009), Iss. 4 : pp. 485–508

Abstract

A convex variational formulation is proposed to solve multicomponent signal processing problems in Hilbert spaces. The cost function consists of a separable term, in which each component is modeled through its own potential, and of a coupling term, in which constraints on linear transformations of the components are penalized with smooth functionals. An algorithm with guaranteed weak convergence to a solution to the problem is provided. Various multicomponent signal decomposition and recovery applications are discussed.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/nmtma.2009.m9009s

Numerical Mathematics: Theory, Methods and Applications, Vol. 2 (2009), Iss. 4 : pp. 485–508

Published online:    2009-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    24

Keywords:    Convex optimization denoising image restoration proximal algorithm signal decomposition signal recovery.

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