@inproceedings{9ffe3d62a6b7441c9c2cbeddedd7600e,
title = "Multidimensional unlimited sampling: A geometrical perspective",
abstract = "The recently introduced unlimited sampling theorem proves that a one-dimensional bandlimited function can be perfectly recovered from a constant factor oversampling of its modulo samples. The advantage of this approach is that arbitrary high-dynamic-range signals can be recovered without sensor saturation or clipping. In this paper, we prove a multidimensional version of the unlimited sampling theorem that works with arbitrary sampling lattices. We also present a geometrical perspective on the emerging class of modulo sampling problem that is based on the topology of quotient spaces.",
keywords = "Lattice theory, Multidimensional signal processing, Quotient spaces, Shannon sampling theory",
author = "Vincent Bouis and Felix Krahmer and Ayush Bhandari",
note = "Publisher Copyright: {\textcopyright} 2021 European Signal Processing Conference, EUSIPCO. All rights reserved.; 28th European Signal Processing Conference, EUSIPCO 2020 ; Conference date: 24-08-2020 Through 28-08-2020",
year = "2021",
month = jan,
day = "24",
doi = "10.23919/Eusipco47968.2020.9287529",
language = "English",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
pages = "2314--2318",
booktitle = "28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings",
}