## Sparse Approximation by Linear Programming using an L1 Data-Fidelity Term

This paper studies the problem of sparse signal approximation over redundant dictionaries. Our attention is focused on the minimization of a cost function where the error is measured by using the L1 norm, giving thus less importance to outliers. We show a constructive equivalence between the proposed minimization problem and Linear Programming. A recovery condition is then provided and an example illustrates the use of such a technique for denoising.

Published in:
Proc. of Workshop on Signal Processing with Adaptative Sparse Structured Representations
Year:
2005
Publisher:
IEEE
Keywords:
Laboratories:

n/a
Rate this document:

1
2
3

(Not yet reviewed)