Unlimited dynamic range signal recovery for folded graph signals

Recovery of a graph signal from samples has many important applications in signal processing over networks and graph-structured data. To capture very high or even unlimited dynamic range signals, modulo sampling has been investigated. Folded signals are signals generated from a modulo operation. In...

Full description

Saved in:
Bibliographic Details
Main Authors: Ji, Feng, Pratibha, Tay, Wee Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/161900
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-161900
record_format dspace
spelling sg-ntu-dr.10356-1619002023-03-31T16:03:03Z Unlimited dynamic range signal recovery for folded graph signals Ji, Feng Pratibha Tay, Wee Peng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Folding ADC Folded Signal Recovery of a graph signal from samples has many important applications in signal processing over networks and graph-structured data. To capture very high or even unlimited dynamic range signals, modulo sampling has been investigated. Folded signals are signals generated from a modulo operation. In this paper, we investigate the problem of recovering bandlimited graph signals from folded signal samples. We derive sufficient conditions to achieve successful recovery of the graph signal, which can be achieved via integer programming. To resolve the scalability issue of integer programming, we propose a sparse optimization recovery method for graph signals satisfying certain technical conditions. Such an approach requires a novel graph sampling scheme that selects vertices with small signal variation. The proposed algorithm exploits the inherent relationship among the graph vertices in both the vertex and time domains to recover the graph signal from folded samples. Simulations and experiments validate the feasibility of our proposed approach. Ministry of Education (MOE) Submitted/Accepted version This work was supported in part by the Singapore Ministry of Education Academic Research Fund Tier 2 grants MOE2018-T2-2-019 (S) and MOE-T2EP20220-0002. 2022-09-26T01:09:26Z 2022-09-26T01:09:26Z 2022 Journal Article Ji, F., Pratibha & Tay, W. P. (2022). Unlimited dynamic range signal recovery for folded graph signals. Signal Processing, 198, 108574-. https://dx.doi.org/10.1016/j.sigpro.2022.108574 0165-1684 https://hdl.handle.net/10356/161900 10.1016/j.sigpro.2022.108574 2-s2.0-85128429557 198 108574 en MOE2018-T2-2-019 (S) MOE-T2EP20220- 0002 Signal Processing © 2022 Elsevier B.V. All rights reserved. This paper was published in Signal Processing and is made available with permission of Elsevier B.V. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Folding ADC
Folded Signal
spellingShingle Engineering::Electrical and electronic engineering
Folding ADC
Folded Signal
Ji, Feng
Pratibha
Tay, Wee Peng
Unlimited dynamic range signal recovery for folded graph signals
description Recovery of a graph signal from samples has many important applications in signal processing over networks and graph-structured data. To capture very high or even unlimited dynamic range signals, modulo sampling has been investigated. Folded signals are signals generated from a modulo operation. In this paper, we investigate the problem of recovering bandlimited graph signals from folded signal samples. We derive sufficient conditions to achieve successful recovery of the graph signal, which can be achieved via integer programming. To resolve the scalability issue of integer programming, we propose a sparse optimization recovery method for graph signals satisfying certain technical conditions. Such an approach requires a novel graph sampling scheme that selects vertices with small signal variation. The proposed algorithm exploits the inherent relationship among the graph vertices in both the vertex and time domains to recover the graph signal from folded samples. Simulations and experiments validate the feasibility of our proposed approach.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Ji, Feng
Pratibha
Tay, Wee Peng
format Article
author Ji, Feng
Pratibha
Tay, Wee Peng
author_sort Ji, Feng
title Unlimited dynamic range signal recovery for folded graph signals
title_short Unlimited dynamic range signal recovery for folded graph signals
title_full Unlimited dynamic range signal recovery for folded graph signals
title_fullStr Unlimited dynamic range signal recovery for folded graph signals
title_full_unstemmed Unlimited dynamic range signal recovery for folded graph signals
title_sort unlimited dynamic range signal recovery for folded graph signals
publishDate 2022
url https://hdl.handle.net/10356/161900
_version_ 1762031100911157248