Non-Negative Orthogonal Greedy Algorithms
| العنوان: | Non-Negative Orthogonal Greedy Algorithms |
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| المؤلفون: | Thanh Thi Nguyen, El-Hadi Djermoune, Charles Soussen, Jerome Idier |
| المساهمون: | Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Laboratoire des Sciences du Numérique de Nantes (LS2N), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Signal, IMage et Son (SIMS ), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), ANR-15-CE23-0021,BECOSE,Au delà de l'échantillonnage compressé : algorithmes d'approximation parcimonieuse pour les problèmes inverses mal conditionnés(2015) |
| المصدر: | IEEE Transactions on Signal Processing IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2019, 67 (21), pp.5643-5658. ⟨10.1109/TSP.2019.2943225⟩ |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Computational complexity theory, Computer science, Signal reconstruction, Approximation algorithm, 020206 networking & telecommunications, non-negative least-squares, 02 engineering and technology, Sparse approximation, orthogonal greedy algorithms, non-negativity, Matching pursuit, sparse reconstruction, active-set algorithms, Non-negative least squares, Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, Deconvolution, Electrical and Electronic Engineering, Greedy algorithm, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithm |
| الوصف: | International audience; Orthogonal greedy algorithms are popular sparse signal reconstruction algorithms. Their principle is to select atoms one by one. A series of unconstrained least-squares subproblems of gradually increasing size is solved to compute the approximation coefficients, which is efficiently performed using a fast recursive update scheme. When dealing with non-negative sparse signal reconstruction, a series of non-negative least-squares subproblems have to be solved. Fast implementation becomes tricky since each subproblem does not have a closed-form solution anymore. Recently, non-negative extensions of the classical orthogonal matching pursuit and orthogonal least squares algorithms were proposed, using slow (i.e., non-recursive) or recursive but inexact implementations. In this paper, we revisit these algorithms in a unified way. We define a class of non-negative orthogonal algorithms and exhibit their structural properties. We propose a fast and exact implementation based on the active-set resolution of non-negative least-squares and exploiting warm start initializations. The algorithms are assessed in terms of accuracy and computational complexity for a sparse spike deconvolution problem. We also present an application to near-infrared spectra decomposition. |
| تدمد: | 1941-0476 1053-587X |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd8d7702678f707f6288b7ac57d38cf3 https://doi.org/10.1109/tsp.2019.2943225 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....bd8d7702678f707f6288b7ac57d38cf3 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19410476 1053587X |
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