Data driven sampling of oscillating signals
Functional Analysis
2014-12-30 v2 Statistics Theory
Statistics Theory
Abstract
The reduction of the number of samples is a key issue in signal processing for mobile applications. We investigate the link between the smoothness properties of a signal and the number of samples that can be obtained through a level crossing sampling procedure. The algorithm is analyzed and an upper bound of the number of samples is obtained in the worst case. The theoretical results are illustrated with applications to fractional Brownian motions and the Weierstrass function.
Keywords
Cite
@article{arxiv.1312.7401,
title = {Data driven sampling of oscillating signals},
author = {Brigitte Bidégaray-Fesquet and Marianne Clausel},
journal= {arXiv preprint arXiv:1312.7401},
year = {2014}
}