Consistency of l1 recovery from noisy deterministic measurements
Optimization and Control
2012-12-04 v1
Abstract
In this paper a new result of recovery of sparse vectors from deterministic and noisy measurements by l1 minimization is given. The sparse vector is randomly chosen and follows a generic p-sparse model introduced by Candes and al. The main theorem ensures consistency of l1 minimization with high probability. This first result is secondly extended to compressible vectors.
Keywords
Cite
@article{arxiv.1212.0369,
title = {Consistency of l1 recovery from noisy deterministic measurements},
author = {Charles Dossal and Rémi Tesson},
journal= {arXiv preprint arXiv:1212.0369},
year = {2012}
}
Comments
9 pages