Identification of Matrices having a Sparse Representation
Numerical Analysis
2015-04-23 v1
Abstract
We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Connections with sparse signal recovery allows for the use of efficient reconstruction techniques such as Basis Pursuit. Of particular interest is the dictionary of time-frequency shift matrices and its role for channel estimation and identification in communications engineering. We present recovery results for Basis Pursuit with the time-frequency shift dictionary and various dictionaries of random matrices.
Cite
@article{arxiv.1504.05807,
title = {Identification of Matrices having a Sparse Representation},
author = {Götz E. Pfander and Holger Rauhut and Jared Tanner},
journal= {arXiv preprint arXiv:1504.05807},
year = {2015}
}