Off-The-Grid Spectral Compressed Sensing With Prior Information
Information Theory
2013-11-08 v2 math.IT
Abstract
Recent research in off-the-grid compressed sensing (CS) has demonstrated that, under certain conditions, one can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. In this paper, we extend off-the-grid CS to applications where some prior information about spectrally sparse signal is known. We specifically consider cases where a few contributing frequencies or poles, but not their amplitudes or phases, are known a priori. Our results show that equipping off-the-grid CS with the known-poles algorithm can increase the probability of recovering all the frequency components.
Keywords
Cite
@article{arxiv.1311.0950,
title = {Off-The-Grid Spectral Compressed Sensing With Prior Information},
author = {Kumar Vijay Mishra and Myung Cho and Anton Kruger and Weiyu Xu},
journal= {arXiv preprint arXiv:1311.0950},
year = {2013}
}
Comments
5 pages, 4 figures