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An optimized version of non-negative OMP

Abstract : This article addresses least-squares minimization under sparsity and non-negativity constraints. We propose a recursive implementation of Non-Negative Orthogonal Matching Pursuit (NNOMP) based on the active set method for solving least-squares subproblems. We further propose an improvement of NNOMP, named support-Shrinkage NNOMP (SNNOMP), based on the shrinkage of the support of iterates when some coordinates vanish. SNNOMP is compared with the existing versions of NNOMP for a sparse deconvolution problem.
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Submitted on : Monday, September 11, 2017 - 1:59:09 PM
Last modification on : Friday, August 5, 2022 - 2:54:51 PM


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  • HAL Id : hal-01585253, version 1


Thi Thanh Nguyen, Charles Soussen, Jérôme Idier, El-Hadi Djermoune. An optimized version of non-negative OMP. XXVIe Colloque GRETSI Traitement du Signal & des Images, GRETSI 2017, Sep 2017, Juan-les-Pins, France. ⟨hal-01585253⟩



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