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Graph Nodal Domains and Data.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Graph Nodal Domains and Data./
Author:
Hamilton, Wesley A.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:
92 p.
Notes:
Source: Dissertations Abstracts International, Volume: 82-12, Section: B.
Contained By:
Dissertations Abstracts International82-12B.
Subject:
Mathematics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28418946
ISBN:
9798516058431
Graph Nodal Domains and Data.
Hamilton, Wesley A.
Graph Nodal Domains and Data.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 92 p.
Source: Dissertations Abstracts International, Volume: 82-12, Section: B.
Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2021.
This item must not be sold to any third party vendors.
This thesis proposes and develops a graph spectral flow for computing nodal counts and nodal deficiencies of graph Laplacian eigenvectors. Background on Laplace eigenfunctions and their nodal domains, as well as the corresponding results in the spectral graph theory literature, is given. We also review some effective tools that adapt spectral methods for the analysis of data, in particular the use of ratio cuts for partitioning and diffusion maps for dimensionality reduction. We then define two versions of the graph spectral flow and develop properties of each, after which examples of the spectral flow on a number of graphs are provided. Finally we mention ongoing lines of research related to both theoretical and applied aspects of graphs' nodal counts.
ISBN: 9798516058431Subjects--Topical Terms:
515831
Mathematics.
Subjects--Index Terms:
Data
Graph Nodal Domains and Data.
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Source: Dissertations Abstracts International, Volume: 82-12, Section: B.
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Advisor: Marzuola, Jeremy L.
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Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2021.
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This item must not be sold to any third party vendors.
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This thesis proposes and develops a graph spectral flow for computing nodal counts and nodal deficiencies of graph Laplacian eigenvectors. Background on Laplace eigenfunctions and their nodal domains, as well as the corresponding results in the spectral graph theory literature, is given. We also review some effective tools that adapt spectral methods for the analysis of data, in particular the use of ratio cuts for partitioning and diffusion maps for dimensionality reduction. We then define two versions of the graph spectral flow and develop properties of each, after which examples of the spectral flow on a number of graphs are provided. Finally we mention ongoing lines of research related to both theoretical and applied aspects of graphs' nodal counts.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28418946
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