Journal article
A new iterative firm-thresholding algorithm for inverse problems with sparsity constraints
Applied and computational harmonic analysis, v 35(1)
Jul 2013
Abstract
In this paper we propose a variation of the soft-thresholding algorithm for finding sparse approximate solutions of the equation Ax=b, where as the sparsity of the iterate increases the penalty function changes. In this approach, sufficiently large entries in a sparse iterate are left untouched. The advantage of this approach is that a higher regularization constant can be used, leading to a significant reduction of the total number of iterations. Numerical experiments for sparse recovery problems, also with noisy data, are included.
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Details
- Title
- A new iterative firm-thresholding algorithm for inverse problems with sparsity constraints
- Creators
- Sergey Voronin - Princeton UniversityHugo J. Woerdeman - Drexel University
- Publication Details
- Applied and computational harmonic analysis, v 35(1)
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:000319709100009
- Scopus ID
- 2-s2.0-84877721688
- Other Identifier
- 991019168684604721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Mathematics, Applied