Výsledky vyhledávání - "iterative-shrinkage algorithms"

Automatic threshold estimation for Iterative Shrinkage Algorithms used with compressed sensing

Publikováno v: ICASSP

Recently, a new class of algorithms has been developed which iteratively build a sparse solution to an underdetermined linear system of equations. These algorithms are known in the literature as Iterative Shrinkage Algorithms (ISA). ISA algorithms de

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ab86bfbc086b4f91beb58edefffe8a85
https://doi.org/10.1109/icassp.2012.6288479

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Iterative-Shrinkage Algorithms

Autor: Michael Elad

Publikováno v: Sparse and Redundant Representations ISBN: 9781441970107

In this chapter, our goal is the minimization of a function of the form $$f\left({\mathbf{x}}\right)=\lambda \mathbf{1}^T \rho{\left({\mathbf{x}}\right)}+\frac{1}{2}\parallel \mathbf{b}-\mathbf{A}\mathbf{x}{\parallel^{2}_{2}},$$ which we have seen be

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3610d765ab07d193082311def463f3e3
https://doi.org/10.1007/978-1-4419-7011-4_6

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Conference

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On the convergence of iterative shrinkage algorithms with adaptive discrepancy terms

Autor: Sandrine Anthoine

Publikováno v: Proceedings of IPIA: Applied Inverse Problems 2007: Theoretical and Computational Aspects.
IPIA: Applied Inverse Problems 2007: Theoretical and Computational Aspects.
IPIA: Applied Inverse Problems 2007: Theoretical and Computational Aspects., Jun 2007, Vancouver, Canada. pp.012008, ⟨10.1088/1742-6596/124/1/012008⟩

International audience; In this paper, the inversion of a linear operator is tackled by a procedure called iterative shrinkage. Iterative shrinkage is a procedure that minimizes a functional balancing quadratic discrepancy terms with Lp regularizatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c41422d168e935c68ae1a1fccedb5af
https://hal.archives-ouvertes.fr/hal-00394191/document

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Akademický článek

Multi-Layered Basis Pursuit Algorithms for Classification of MR Images of Knee ACL Tear

Autor: Abdul Wahid, Jawad Ali Shah, Adnan Umar Khan, Mukhtar Ullah, Mohd Zaki Ayob

Publikováno v: IEEE Access, Vol 8, Pp 205424-205435 (2020)

Deep learning architectures have been extensively used in recent years for the classification of biomedical images to assist clinicians for diagnosis and treatment management of patients with different health conditions. These architectures have demo

Externí odkaz: https://doaj.org/article/091ac545b21d4301a35bc141ed52c44a

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