A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging

This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or fra...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Biomedical physics & engineering express 2022-11, Vol.8 (6), p.65010
Hauptverfasser:	Caracciolo, S F, Caiafa, C F, Martínez Pería, F D, Arini, P D
Format:	Artikel
Sprache:	eng
Schlagworte:	ECGI group lasso Kronecker product sparse regularization
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page
container_issue	6
container_start_page	65010
container_title	Biomedical physics & engineering express
container_volume	8
creator	Caracciolo, S F Caiafa, C F Martínez Pería, F D Arini, P D
description	This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.
doi_str_mv	10.1088/2057-1976/ac835b
format	Article
fullrecord	<record><control><sourceid>proquest_iop_j</sourceid><recordid>TN_cdi_proquest_miscellaneous_2693774663</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2693774663</sourcerecordid><originalsourceid>FETCH-LOGICAL-c298t-8da650abfa248ccdba5187dcfd66ae3eec5036fd14444c33112d30716c1f292c3</originalsourceid><addsrcrecordid>eNp1kE1P3DAQhiNEpSLg3qNv9NAtdrxxkiNClCIhcaFnazK2s15lY3fs5ePaX15HWyEOxRd7rPd9NHqq6ovg3wXvusuaN-1K9K26BOxkMxxVJ29fx-_en6vzlLacc6FqpfrmpPpzxRykzGAaA_m82TEXiKUI2YdsdzEQTCz5cYYpMbIYniy9sn3y88iABp8Jymw8lvwM5G1izwXDIMbJ40KZWQ7MThYzBQQyPowEceOR-R2MhXNWfXKFbs__3afVrx83j9c_V_cPt3fXV_crrPsurzoDquEwOKjXHaIZoBFda9AZpcBKa7HhUjkj1uWglELURvJWKBSu7muUp9XXAzdS-L23KeudT2inCWYb9knXqpdtu1ZKlig_RJFCSmSdjlS2pVctuF6M60WpXpTqg_FSuThUfIh6G_a0GNNDtC-600rzsnvpRuNK8tt_kh-C_wKx_pOn</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2693774663</pqid></control><display><type>article</type><title>A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging</title><source>IOP Publishing Journals</source><source>Institute of Physics (IOP) Journals - HEAL-Link</source><creator>Caracciolo, S F ; Caiafa, C F ; Martínez Pería, F D ; Arini, P D</creator><creatorcontrib>Caracciolo, S F ; Caiafa, C F ; Martínez Pería, F D ; Arini, P D</creatorcontrib><description>This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.</description><identifier>ISSN: 2057-1976</identifier><identifier>EISSN: 2057-1976</identifier><identifier>DOI: 10.1088/2057-1976/ac835b</identifier><language>eng</language><publisher>IOP Publishing</publisher><subject>ECGI ; group lasso ; Kronecker product ; sparse regularization</subject><ispartof>Biomedical physics & engineering express, 2022-11, Vol.8 (6), p.65010</ispartof><rights>2022 IOP Publishing Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c298t-8da650abfa248ccdba5187dcfd66ae3eec5036fd14444c33112d30716c1f292c3</cites><orcidid>0000-0001-5437-6095 ; 0000-0002-6347-7186 ; 0000-0003-2181-0507 ; 0000-0002-5548-7528</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/2057-1976/ac835b/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>314,776,780,27901,27902,53821,53868</link.rule.ids></links><search><creatorcontrib>Caracciolo, S F</creatorcontrib><creatorcontrib>Caiafa, C F</creatorcontrib><creatorcontrib>Martínez Pería, F D</creatorcontrib><creatorcontrib>Arini, P D</creatorcontrib><title>A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging</title><title>Biomedical physics & engineering express</title><addtitle>BPEX</addtitle><addtitle>Biomed. Phys. Eng. Express</addtitle><description>This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.</description><subject>ECGI</subject><subject>group lasso</subject><subject>Kronecker product</subject><subject>sparse regularization</subject><issn>2057-1976</issn><issn>2057-1976</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kE1P3DAQhiNEpSLg3qNv9NAtdrxxkiNClCIhcaFnazK2s15lY3fs5ePaX15HWyEOxRd7rPd9NHqq6ovg3wXvusuaN-1K9K26BOxkMxxVJ29fx-_en6vzlLacc6FqpfrmpPpzxRykzGAaA_m82TEXiKUI2YdsdzEQTCz5cYYpMbIYniy9sn3y88iABp8Jymw8lvwM5G1izwXDIMbJ40KZWQ7MThYzBQQyPowEceOR-R2MhXNWfXKFbs__3afVrx83j9c_V_cPt3fXV_crrPsurzoDquEwOKjXHaIZoBFda9AZpcBKa7HhUjkj1uWglELURvJWKBSu7muUp9XXAzdS-L23KeudT2inCWYb9knXqpdtu1ZKlig_RJFCSmSdjlS2pVctuF6M60WpXpTqg_FSuThUfIh6G_a0GNNDtC-600rzsnvpRuNK8tt_kh-C_wKx_pOn</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Caracciolo, S F</creator><creator>Caiafa, C F</creator><creator>Martínez Pería, F D</creator><creator>Arini, P D</creator><general>IOP Publishing</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5437-6095</orcidid><orcidid>https://orcid.org/0000-0002-6347-7186</orcidid><orcidid>https://orcid.org/0000-0003-2181-0507</orcidid><orcidid>https://orcid.org/0000-0002-5548-7528</orcidid></search><sort><creationdate>20221101</creationdate><title>A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging</title><author>Caracciolo, S F ; Caiafa, C F ; Martínez Pería, F D ; Arini, P D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c298t-8da650abfa248ccdba5187dcfd66ae3eec5036fd14444c33112d30716c1f292c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>ECGI</topic><topic>group lasso</topic><topic>Kronecker product</topic><topic>sparse regularization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Caracciolo, S F</creatorcontrib><creatorcontrib>Caiafa, C F</creatorcontrib><creatorcontrib>Martínez Pería, F D</creatorcontrib><creatorcontrib>Arini, P D</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Biomedical physics & engineering express</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Caracciolo, S F</au><au>Caiafa, C F</au><au>Martínez Pería, F D</au><au>Arini, P D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging</atitle><jtitle>Biomedical physics & engineering express</jtitle><stitle>BPEX</stitle><addtitle>Biomed. Phys. Eng. Express</addtitle><date>2022-11-01</date><risdate>2022</risdate><volume>8</volume><issue>6</issue><spage>65010</spage><pages>65010-</pages><issn>2057-1976</issn><eissn>2057-1976</eissn><abstract>This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution.</abstract><pub>IOP Publishing</pub><doi>10.1088/2057-1976/ac835b</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5437-6095</orcidid><orcidid>https://orcid.org/0000-0002-6347-7186</orcidid><orcidid>https://orcid.org/0000-0003-2181-0507</orcidid><orcidid>https://orcid.org/0000-0002-5548-7528</orcidid></addata></record>
fulltext	fulltext
identifier	ISSN: 2057-1976
ispartof	Biomedical physics & engineering express, 2022-11, Vol.8 (6), p.65010
issn	2057-1976 2057-1976
language	eng
recordid	cdi_proquest_miscellaneous_2693774663
source	IOP Publishing Journals; Institute of Physics (IOP) Journals - HEAL-Link
subjects	ECGI group lasso Kronecker product sparse regularization
title	A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T11%3A21%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_iop_j&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20fast%20algorithm%20for%20spatiotemporal%20signals%20recovery%20using%20arbitrary%20dictionaries%20with%20application%20to%20electrocardiographic%20imaging&rft.jtitle=Biomedical%20physics%20&%20engineering%20express&rft.au=Caracciolo,%20S%20F&rft.date=2022-11-01&rft.volume=8&rft.issue=6&rft.spage=65010&rft.pages=65010-&rft.issn=2057-1976&rft.eissn=2057-1976&rft_id=info:doi/10.1088/2057-1976/ac835b&rft_dat=%3Cproquest_iop_j%3E2693774663%3C/proquest_iop_j%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2693774663&rft_id=info:pmid/&rfr_iscdi=true