An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint
Information Theory
2020-12-03 v1 math.IT
Abstract
Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding non-convex functional based on a projected gradient descent coupled with an initialization procedure. We give qualitative insights on the theoretical foundations of the algorithm and provide experiments showing its potential for imaging problems.
Cite
@article{arxiv.2012.01262,
title = {An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint},
author = {Yann Traonmilin and Jean-François Aujol and Arhur Leclaire},
journal= {arXiv preprint arXiv:2012.01262},
year = {2020}
}
Comments
in Proceedings of iTWIST'20, Paper-ID: 7, Nantes, France, December, 2-4, 2020. arXiv admin note: substantial text overlap with arXiv:2005.05920