Loading…

Partition of Unity Methods for Signal Processing on Graphs

Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be co...

Full description

Saved in:
Bibliographic Details
Published in:The Journal of fourier analysis and applications 2021-08, Vol.27 (4), Article 66
Main Authors: Cavoretto, Roberto, De Rossi, Alessandra, Erb, Wolfgang
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783
cites cdi_FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783
container_end_page
container_issue 4
container_start_page
container_title The Journal of fourier analysis and applications
container_volume 27
creator Cavoretto, Roberto
De Rossi, Alessandra
Erb, Wolfgang
description Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be combined with a local graph basis function (GBF) approximation method in order to obtain low-cost global interpolation or classification schemes. From a theoretical point of view, we study necessary prerequisites for the partition of unity such that global error estimates of the PUM follow from corresponding local ones. Finally, properties of the PUM as cost-efficiency and approximation accuracy are investigated numerically.
doi_str_mv 10.1007/s00041-021-09871-w
format article
fullrecord <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2553536295</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A718418334</galeid><sourcerecordid>A718418334</sourcerecordid><originalsourceid>FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWKt_wNOC562T78RbKVqFigXtOaS72Tal3dRkS-m_N7qCNwlDhuF5huFF6BbDCAPI-wQADJdAcmklcXk8QwPMKS654vg89yB07oW-RFcpbSCTVNIBepjb2PnOh7YITbFofXcqXl23DnUqmhCLd79q7baYx1C5lHy7KjI5jXa_TtfoorHb5G5-_yFaPD1-TJ7L2dv0ZTKelRXlqistMFBLUfNaMouFto1kRFSSUG41sZgB4coyyYDXQjHn5JIwrQUDJgiTig7RXb93H8PnwaXObMIh5quSIZxTTgXRPFOjnlrZrTO-bUIXbZVf7Xa-Cq1rfJ6PJVYMK0pZFkgvVDGkFF1j9tHvbDwZDOY7VNOHanJU5idUc8wS7aWU4Xbl4t8t_1hfmLJ3Pw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2553536295</pqid></control><display><type>article</type><title>Partition of Unity Methods for Signal Processing on Graphs</title><source>Springer Nature</source><creator>Cavoretto, Roberto ; De Rossi, Alessandra ; Erb, Wolfgang</creator><creatorcontrib>Cavoretto, Roberto ; De Rossi, Alessandra ; Erb, Wolfgang</creatorcontrib><description>Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be combined with a local graph basis function (GBF) approximation method in order to obtain low-cost global interpolation or classification schemes. From a theoretical point of view, we study necessary prerequisites for the partition of unity such that global error estimates of the PUM follow from corresponding local ones. Finally, properties of the PUM as cost-efficiency and approximation accuracy are investigated numerically.</description><identifier>ISSN: 1069-5869</identifier><identifier>EISSN: 1531-5851</identifier><identifier>DOI: 10.1007/s00041-021-09871-w</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Abstract Harmonic Analysis ; Approximation ; Approximations and Expansions ; Basis functions ; Clustering ; Fourier Analysis ; Graphs ; Harmonic Analysis on Combinatorial Graphs ; Interpolation ; Mathematical analysis ; Mathematical Methods in Physics ; Mathematics ; Mathematics and Statistics ; Methods ; Partial Differential Equations ; Signal processing ; Signal,Image and Speech Processing ; Unity</subject><ispartof>The Journal of fourier analysis and applications, 2021-08, Vol.27 (4), Article 66</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>COPYRIGHT 2021 Springer</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783</citedby><cites>FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783</cites><orcidid>0000-0003-1285-3820 ; 0000-0003-3541-5401 ; 0000-0001-6076-4115</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Cavoretto, Roberto</creatorcontrib><creatorcontrib>De Rossi, Alessandra</creatorcontrib><creatorcontrib>Erb, Wolfgang</creatorcontrib><title>Partition of Unity Methods for Signal Processing on Graphs</title><title>The Journal of fourier analysis and applications</title><addtitle>J Fourier Anal Appl</addtitle><description>Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be combined with a local graph basis function (GBF) approximation method in order to obtain low-cost global interpolation or classification schemes. From a theoretical point of view, we study necessary prerequisites for the partition of unity such that global error estimates of the PUM follow from corresponding local ones. Finally, properties of the PUM as cost-efficiency and approximation accuracy are investigated numerically.</description><subject>Abstract Harmonic Analysis</subject><subject>Approximation</subject><subject>Approximations and Expansions</subject><subject>Basis functions</subject><subject>Clustering</subject><subject>Fourier Analysis</subject><subject>Graphs</subject><subject>Harmonic Analysis on Combinatorial Graphs</subject><subject>Interpolation</subject><subject>Mathematical analysis</subject><subject>Mathematical Methods in Physics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Methods</subject><subject>Partial Differential Equations</subject><subject>Signal processing</subject><subject>Signal,Image and Speech Processing</subject><subject>Unity</subject><issn>1069-5869</issn><issn>1531-5851</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWKt_wNOC562T78RbKVqFigXtOaS72Tal3dRkS-m_N7qCNwlDhuF5huFF6BbDCAPI-wQADJdAcmklcXk8QwPMKS654vg89yB07oW-RFcpbSCTVNIBepjb2PnOh7YITbFofXcqXl23DnUqmhCLd79q7baYx1C5lHy7KjI5jXa_TtfoorHb5G5-_yFaPD1-TJ7L2dv0ZTKelRXlqistMFBLUfNaMouFto1kRFSSUG41sZgB4coyyYDXQjHn5JIwrQUDJgiTig7RXb93H8PnwaXObMIh5quSIZxTTgXRPFOjnlrZrTO-bUIXbZVf7Xa-Cq1rfJ6PJVYMK0pZFkgvVDGkFF1j9tHvbDwZDOY7VNOHanJU5idUc8wS7aWU4Xbl4t8t_1hfmLJ3Pw</recordid><startdate>20210801</startdate><enddate>20210801</enddate><creator>Cavoretto, Roberto</creator><creator>De Rossi, Alessandra</creator><creator>Erb, Wolfgang</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-1285-3820</orcidid><orcidid>https://orcid.org/0000-0003-3541-5401</orcidid><orcidid>https://orcid.org/0000-0001-6076-4115</orcidid></search><sort><creationdate>20210801</creationdate><title>Partition of Unity Methods for Signal Processing on Graphs</title><author>Cavoretto, Roberto ; De Rossi, Alessandra ; Erb, Wolfgang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Abstract Harmonic Analysis</topic><topic>Approximation</topic><topic>Approximations and Expansions</topic><topic>Basis functions</topic><topic>Clustering</topic><topic>Fourier Analysis</topic><topic>Graphs</topic><topic>Harmonic Analysis on Combinatorial Graphs</topic><topic>Interpolation</topic><topic>Mathematical analysis</topic><topic>Mathematical Methods in Physics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Methods</topic><topic>Partial Differential Equations</topic><topic>Signal processing</topic><topic>Signal,Image and Speech Processing</topic><topic>Unity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cavoretto, Roberto</creatorcontrib><creatorcontrib>De Rossi, Alessandra</creatorcontrib><creatorcontrib>Erb, Wolfgang</creatorcontrib><collection>CrossRef</collection><jtitle>The Journal of fourier analysis and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cavoretto, Roberto</au><au>De Rossi, Alessandra</au><au>Erb, Wolfgang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Partition of Unity Methods for Signal Processing on Graphs</atitle><jtitle>The Journal of fourier analysis and applications</jtitle><stitle>J Fourier Anal Appl</stitle><date>2021-08-01</date><risdate>2021</risdate><volume>27</volume><issue>4</issue><artnum>66</artnum><issn>1069-5869</issn><eissn>1531-5851</eissn><abstract>Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be combined with a local graph basis function (GBF) approximation method in order to obtain low-cost global interpolation or classification schemes. From a theoretical point of view, we study necessary prerequisites for the partition of unity such that global error estimates of the PUM follow from corresponding local ones. Finally, properties of the PUM as cost-efficiency and approximation accuracy are investigated numerically.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s00041-021-09871-w</doi><orcidid>https://orcid.org/0000-0003-1285-3820</orcidid><orcidid>https://orcid.org/0000-0003-3541-5401</orcidid><orcidid>https://orcid.org/0000-0001-6076-4115</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1069-5869
ispartof The Journal of fourier analysis and applications, 2021-08, Vol.27 (4), Article 66
issn 1069-5869
1531-5851
language eng
recordid cdi_proquest_journals_2553536295
source Springer Nature
subjects Abstract Harmonic Analysis
Approximation
Approximations and Expansions
Basis functions
Clustering
Fourier Analysis
Graphs
Harmonic Analysis on Combinatorial Graphs
Interpolation
Mathematical analysis
Mathematical Methods in Physics
Mathematics
Mathematics and Statistics
Methods
Partial Differential Equations
Signal processing
Signal,Image and Speech Processing
Unity
title Partition of Unity Methods for Signal Processing on Graphs
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T23%3A55%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Partition%20of%20Unity%20Methods%20for%20Signal%20Processing%20on%20Graphs&rft.jtitle=The%20Journal%20of%20fourier%20analysis%20and%20applications&rft.au=Cavoretto,%20Roberto&rft.date=2021-08-01&rft.volume=27&rft.issue=4&rft.artnum=66&rft.issn=1069-5869&rft.eissn=1531-5851&rft_id=info:doi/10.1007/s00041-021-09871-w&rft_dat=%3Cgale_proqu%3EA718418334%3C/gale_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c358t-a0408b6d5d74a169af7426c7235a92a140258a47405d684ee7b24996404624783%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2553536295&rft_id=info:pmid/&rft_galeid=A718418334&rfr_iscdi=true