Submatrices with non-uniformly selected random supports and insights into sparse approximation
Probability
2020-12-04 v1
Abstract
In this paper we derive tail bounds on the norms of random submatrices with non-uniformly distributed supports. We apply these results to sparse approximation and conduct an analysis of the average case performance of thresholding, Orthogonal Matching Pursuit and Basis Pursuit. As an application of these results we characterise sensing dictionaries to improve average performance in the non-uniform case and test their performance numerically.
Cite
@article{arxiv.2012.02082,
title = {Submatrices with non-uniformly selected random supports and insights into sparse approximation},
author = {Simon Ruetz and Karin Schnass},
journal= {arXiv preprint arXiv:2012.02082},
year = {2020}
}