A new iterative firm-thresholding algorithm for inverse problems with sparsity constraints

DOI10.1016/j.acha.2012.08.004zbMath1294.65039OpenAlexW1973376681MaRDI QIDQ2252134

Hugo J. Woerdeman, Sergey Voronin

Publication date: 16 July 2014

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.acha.2012.08.004

zbMATH Keywords

inverse problemregularizationnumerical experimentsparsitycompressed sensingthresholding algorithmfirm thresholding

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Ill-posedness and regularization problems in numerical linear algebra (65F22) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Inverse problems in linear algebra (15A29) Iterative numerical methods for linear systems (65F10)

Related Items (3)

A solution approach for cardinality minimization problem based on fractional programming ⋮ Parametrized quasi-soft thresholding operator for compressed sensing and matrix completion ⋮ Optimal $k$-Thresholding Algorithms for Sparse Optimization Problems

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Iterative thresholding algorithms
• The application of joint sparsity and total variation minimization algorithms to a real-life art restoration problem
• Decoding by Linear Programming
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization
• Compressed sensing

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