Imperial College London
Portrait Picture

Dr. Ayush Bhandari

Faculty of Engineering, Department of Electrical and Electronic Engineering

Senior Lecturer
 
 
 
//

Contact

 

+44 (0)20 7594 6233a.bhandari Website

 
 
//

Location

 

802Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Bhandari:2022:10.1109/LSP.2022.3161865,
author = {Bhandari, A},
doi = {10.1109/LSP.2022.3161865},
journal = {IEEE Signal Processing Letters},
pages = {1047--1051},
title = {Back in the US-SR: unlimited sampling and sparse super-resolution with Its hardware validation},
url = {http://dx.doi.org/10.1109/LSP.2022.3161865},
volume = {29},
year = {2022}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The Unlimited Sensing Framework (USF) is a digital acquisition protocol that allows for sampling and reconstruction of high dynamic range signals. By acquiring modulo samples, the USF circumvents the clipping or saturation problem that is a fundamental bottleneck in conventional analog-to-digital converters (ADCs). In the context of the USF, several works have focused on bandlimited function classes and recently, a hardware validation of the modulo sampling approach has been presented. In a different direction, in this paper we focus on non-bandlimited function classes and consider the well-known super-resolution problem; we study the recovery of sparse signals (Dirac impulses) from low-pass filtered, modulo samples. Taking an end-to-end approach to USF based super-resolution, we present a novel recovery algorithm (US-SR) that leverages a doubly sparse structure of the modulo samples. We derive a sampling criterion for the US-SR method. A hardware experiment with the modulo ADC demonstrates the empirical robustness of our method in a realistic, noisy setting, thus validating its practical utility.
AU  - Bhandari,A
DO  - 10.1109/LSP.2022.3161865
EP  - 1051
PY  - 2022///
SN  - 1070-9908
SP  - 1047
TI  - Back in the US-SR: unlimited sampling and sparse super-resolution with Its hardware validation
T2  - IEEE Signal Processing Letters
UR  - http://dx.doi.org/10.1109/LSP.2022.3161865
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000790810400001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/9740441
UR  - http://hdl.handle.net/10044/1/98482
VL  - 29
ER  -
Download