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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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摘要 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. 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.
出处 《Numerical Mathematics(Theory,Methods and Applications)》 SCIE 2009年第4期485-508,共24页 高等学校计算数学学报(英文版)
基金 supported by the Agence Nationale de la Recherche under grant ANR-08-BLAN-0294-02
关键词 Convex optimization DENOISING image restoration proximal algorithm signal decom-position signal recovery 信号分解 变分形式 耦合 光滑 多组分 多分量信号 空间处理 希尔伯特
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