Reconstructing Graph Signals from Noisy Dynamical Samples

Fuente: arXiv
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Autori principali: Aldroubi, Akram, Bailey, Victor, Krishtal, Ilya, Miller, Brendan, Petrosyan, Armenak
Natura: Preprint
Pubblicazione: 2024
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author Aldroubi, Akram
Bailey, Victor
Krishtal, Ilya
Miller, Brendan
Petrosyan, Armenak
author_facet Aldroubi, Akram
Bailey, Victor
Krishtal, Ilya
Miller, Brendan
Petrosyan, Armenak
contents We investigate the dynamical sampling space-time trade-off problem within a graph setting. Specifically, we derive necessary and sufficient conditions for space-time sampling that enable the reconstruction of an initial band-limited signal on a graph. Additionally, we develop and test numerical algorithms for approximating the optimal placement of sensors on the graph to minimize the mean squared error when recovering signals from time-space measurements corrupted by i.i.d.~additive noise. Our numerical experiments demonstrate that our approach outperforms previously proposed algorithms for related problems.
format Preprint
id arxiv_https___arxiv_org_abs_2411_12670
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reconstructing Graph Signals from Noisy Dynamical Samples
Aldroubi, Akram
Bailey, Victor
Krishtal, Ilya
Miller, Brendan
Petrosyan, Armenak
Information Theory
We investigate the dynamical sampling space-time trade-off problem within a graph setting. Specifically, we derive necessary and sufficient conditions for space-time sampling that enable the reconstruction of an initial band-limited signal on a graph. Additionally, we develop and test numerical algorithms for approximating the optimal placement of sensors on the graph to minimize the mean squared error when recovering signals from time-space measurements corrupted by i.i.d.~additive noise. Our numerical experiments demonstrate that our approach outperforms previously proposed algorithms for related problems.
title Reconstructing Graph Signals from Noisy Dynamical Samples
topic Information Theory
url https://arxiv.org/abs/2411.12670