Unlimited sampling with sparse outliers: experiments with impulsive and jump or reset noise
File(s)
Accepted version
Author(s)
Bhandari, Ayush
Type
Conference Paper
Abstract
Unlimited Sensing is a sampling protocol that recovers high dynamic range input signals from their low dynamic range, modulo samples. Bridging the gap between theory and practice, recently, a hardware validation of the unlimited sampling method was presented. Taking another step in this direction, in this paper, we study the problem of recovery from modulo samples contaminated by sparse outliers (noise). Our hardware experiments suggest that impulsive and jump or reset noise can be sources of sparse outliers in the measurements. Such a noise model has not been considered in literature and can lead to the breakdown of the conventional recovery methods. To overcome this problem, we present a mathematically guaranteed algorithm that is based on spectral estimation. Our method perfectly recovers the signal (up to a constant) when the sampling criterion is met and no other noise sources are present. In real experiments where quantization and system noise (e.g. additive Gaussian) play a role, our approach offers a competitive performance. Hardware experiments with our modulo ADC validate the practical utility of our method.
Date Issued
2022-04-27
Date Acceptance
2022-05-01
Citation
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp.5403-5407
ISSN
1520-6149
Publisher
IEEE
Start Page
5403
End Page
5407
Journal / Book Title
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Copyright Statement
Copyright © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000864187905139&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Source
47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Subjects
Acoustics
ADC
Computer Science
Computer Science, Artificial Intelligence
Engineering
Engineering, Electrical & Electronic
modulo
non-linear reconstruction
Prony's method
sampling
Science & Technology
super-resolution
Technology
Publication Status
Published
Start Date
2022-05-22
Finish Date
2022-05-27
Coverage Spatial
Singapore