Multidimensional unlimited sampling: A geometrical perspective

Vincent Bouis, Felix Krahmer, Ayush Bhandari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

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.

Original languageEnglish
Title of host publication28th European Signal Processing Conference, EUSIPCO 2020 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2314-2318
Number of pages5
ISBN (Electronic)9789082797053
DOIs
StatePublished - 24 Jan 2021
Event28th European Signal Processing Conference, EUSIPCO 2020 - Amsterdam, Netherlands
Duration: 24 Aug 202028 Aug 2020

Publication series

NameEuropean Signal Processing Conference
Volume2021-January
ISSN (Print)2219-5491

Conference

Conference28th European Signal Processing Conference, EUSIPCO 2020
Country/TerritoryNetherlands
CityAmsterdam
Period24/08/2028/08/20

Keywords

  • Lattice theory
  • Multidimensional signal processing
  • Quotient spaces
  • Shannon sampling theory

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