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Bibliographic Details
Main Authors: Bodmann, Bernhard G., May, Jennifer J.
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2305.02635
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author Bodmann, Bernhard G.
May, Jennifer J.
author_facet Bodmann, Bernhard G.
May, Jennifer J.
contents The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and find bounds on the time parameter governing the evolution under the heat semigroup that guarantee a successful recovery. This result can be viewed as a type of deconvolution on a graph. A first main result addresses the setting of a common time parameter for all the heat kernels. We also treat a more general setting when the time parameter depends on the location at which the heat kernel is centered.
format Preprint
id arxiv_https___arxiv_org_abs_2305_02635
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Deconvolution on graphs via linear programming
Bodmann, Bernhard G.
May, Jennifer J.
Functional Analysis
47D07, 49N45
The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and find bounds on the time parameter governing the evolution under the heat semigroup that guarantee a successful recovery. This result can be viewed as a type of deconvolution on a graph. A first main result addresses the setting of a common time parameter for all the heat kernels. We also treat a more general setting when the time parameter depends on the location at which the heat kernel is centered.
title Deconvolution on graphs via linear programming
topic Functional Analysis
47D07, 49N45
url https://arxiv.org/abs/2305.02635