On Unlimited Sampling
Ayush Bhandari, Felix Krahmer, Ramesh Raskar

TL;DR
This paper introduces a novel sampling approach using modulo ADCs that can recover signals beyond traditional dynamic range limits, supported by theoretical conditions and a stable recovery algorithm.
Contribution
It provides the first theoretical analysis and recovery algorithm for signals sampled with modulo ADCs, enabling perfect reconstruction of signals with arbitrary amplitudes.
Findings
Perfect recovery of signals with large amplitudes demonstrated.
Theoretical conditions for stable recovery established.
Numerical experiments confirm practical effectiveness.
Abstract
Shannon's sampling theorem provides a link between the continuous and the discrete realms stating that bandlimited signals are uniquely determined by its values on a discrete set. This theorem is realized in practice using so called analog--to--digital converters (ADCs). Unlike Shannon's sampling theorem, the ADCs are limited in dynamic range. Whenever a signal exceeds some preset threshold, the ADC saturates, resulting in aliasing due to clipping. The goal of this paper is to analyze an alternative approach that does not suffer from these problems. Our work is based on recent developments in ADC design, which allow for ADCs that reset rather than to saturate, thus producing modulo samples. An open problem that remains is: Given such modulo samples of a bandlimited function as well as the dynamic range of the ADC, how can the original signal be recovered and what are the sufficient…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
