Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4605117 | Applied and Computational Harmonic Analysis | 2013 | 14 Pages |
Abstract
In this paper we propose a variation of the soft-thresholding algorithm for finding sparse approximate solutions of the equation Ax=bAx=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.
Related Topics
Physical Sciences and Engineering
Mathematics
Analysis
Authors
Sergey Voronin, Hugo J. Woerdeman,