Small coherence implies the weak Null Space Property
Statistics Theory
2016-06-30 v1 Machine Learning
Statistics Theory
Abstract
In the Compressed Sensing community, it is well known that given a matrix with normalized columns, the Restricted Isometry Property (RIP) implies the Null Space Property (NSP). It is also well known that a small Coherence implies a weak RIP, i.e. the singular values of lie between and for "most" index subsets with size governed by and . In this short note, we show that a small Coherence implies a weak Null Space Property, i.e. for most with cardinality . We moreover prove some singular value perturbation bounds that may also prove useful for other applications.
Cite
@article{arxiv.1606.09193,
title = {Small coherence implies the weak Null Space Property},
author = {Stéphane Chrétien and Zhen Wai Olivier Ho},
journal= {arXiv preprint arXiv:1606.09193},
year = {2016}
}