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### Cite Details

Paul Rodríguez and Brendt Wohlberg, "An Efficient Algorithm for Sparse Representations with p Data Fidelity Term", in Proceedings of 4th IEEE Andean Technical Conference (ANDESCON), (Cusco, Perú), Oct 2008

### Abstract

Basis Pursuit (BP) and Basis Pursuit Denoising (BPDN), well established techniques for computing sparse representations, minimize an 2 data fidelity term, subject to an 1 sparsity constraint or regularization term, by mapping the problem to a linear or quadratic program. BPDN with an 1 data fidelity term has recently been proposed, also implemented via a mapping to a linear program. We introduce an alternative approach via an Iteratively Reweighted Least Squares algorithm, providing computational advantages and greater flexibility in the choice of data fidelity term norm.

### BibTeX Entry

@inproceedings{rodriguez-2008-sparse,
author = {Paul Rodr\'{i}guez and Brendt Wohlberg},
title = {An Efficient Algorithm for Sparse Representations with $\ell^{p}$ Data Fidelity Term},
year = {2008},
month = Oct,
urlpdf = {http://brendt.wohlberg.net/publications/pdf/rodriguez-2008-sparse.pdf},
booktitle = {Proceedings of 4th IEEE Andean Technical Conference (ANDESCON)},