Simulated Annealing for Independent Component Analysis Over Galois Fields

Independent Component Analysis over finite fields is an unsupervised signal processing problem that poses a challenging combinatorial optimization task. In this context, a solution based on Simulated Annealing, with an entropy-based objective function, is proposed. The empirical results demonstrate...

Full description

Saved in:
Bibliographic Details
Published in:IEEE signal processing letters 2018-04, Vol.25 (4), p.516-520
Main Authors: Silva, Daniel G., Attux, Romis
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Combinatorial optimization
Correlation
Cost function
Entropy
finite fields
Independent Component Analysis (ICA)
Signal processing algorithms
Simulated annealing
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-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873
cites cdi_FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873
container_end_page 520
container_issue 4
container_start_page 516
container_title IEEE signal processing letters
container_volume 25
creator Silva, Daniel G.
Attux, Romis
description Independent Component Analysis over finite fields is an unsupervised signal processing problem that poses a challenging combinatorial optimization task. In this context, a solution based on Simulated Annealing, with an entropy-based objective function, is proposed. The empirical results demonstrate the effectiveness of the method, with a performance competitive or superior to that of the reference techniques, at an inferior asymptotic computational cost.
doi_str_mv 10.1109/LSP.2018.2803619
format article
fullrecord <record><control><sourceid>crossref_ieee_</sourceid><recordid>TN_cdi_ieee_primary_8286927</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8286927</ieee_id><sourcerecordid>10_1109_LSP_2018_2803619</sourcerecordid><originalsourceid>FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873</originalsourceid><addsrcrecordid>eNo9kE1rg0AQhpfSQtO090Iv_gHt7Ie6HkWaRBBSSHuWVWeLZV3FtYX8-64k9DLzDMw7DA8hzxQiSiF7rU7vEQMqIyaBJzS7IRsaxzJkfrj1DCmEWQbynjw49w0Aksp4Q8pTP_wYtWAX5NaiMr39CvQ4B6XtcEJf7BIU4zCNdqXcKnN2vQuOvzgHe2VGz7seTeceyZ1WxuHTtW_J5-7toziE1XFfFnkVtizhS8gZ19iITrcqAZpkMdfAY9ZqlNq_ioIr3aUomcAUBdVNLBpIWgQQ2CiZ8i2By912Hp2bUdfT3A9qPtcU6lVF7VXUq4r6qsJHXi6RHhH_1yWTScZS_gek_lse</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Simulated Annealing for Independent Component Analysis Over Galois Fields</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Silva, Daniel G. ; Attux, Romis</creator><creatorcontrib>Silva, Daniel G. ; Attux, Romis</creatorcontrib><description>Independent Component Analysis over finite fields is an unsupervised signal processing problem that poses a challenging combinatorial optimization task. In this context, a solution based on Simulated Annealing, with an entropy-based objective function, is proposed. The empirical results demonstrate the effectiveness of the method, with a performance competitive or superior to that of the reference techniques, at an inferior asymptotic computational cost.</description><identifier>ISSN: 1070-9908</identifier><identifier>EISSN: 1558-2361</identifier><identifier>DOI: 10.1109/LSP.2018.2803619</identifier><identifier>CODEN: ISPLEM</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Combinatorial optimization ; Correlation ; Cost function ; Entropy ; finite fields ; Independent Component Analysis (ICA) ; Signal processing algorithms ; Simulated annealing</subject><ispartof>IEEE signal processing letters, 2018-04, Vol.25 (4), p.516-520</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873</citedby><cites>FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873</cites><orcidid>0000-0003-2858-1110</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8286927$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,54795</link.rule.ids></links><search><creatorcontrib>Silva, Daniel G.</creatorcontrib><creatorcontrib>Attux, Romis</creatorcontrib><title>Simulated Annealing for Independent Component Analysis Over Galois Fields</title><title>IEEE signal processing letters</title><addtitle>LSP</addtitle><description>Independent Component Analysis over finite fields is an unsupervised signal processing problem that poses a challenging combinatorial optimization task. In this context, a solution based on Simulated Annealing, with an entropy-based objective function, is proposed. The empirical results demonstrate the effectiveness of the method, with a performance competitive or superior to that of the reference techniques, at an inferior asymptotic computational cost.</description><subject>Algorithm design and analysis</subject><subject>Combinatorial optimization</subject><subject>Correlation</subject><subject>Cost function</subject><subject>Entropy</subject><subject>finite fields</subject><subject>Independent Component Analysis (ICA)</subject><subject>Signal processing algorithms</subject><subject>Simulated annealing</subject><issn>1070-9908</issn><issn>1558-2361</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo9kE1rg0AQhpfSQtO090Iv_gHt7Ie6HkWaRBBSSHuWVWeLZV3FtYX8-64k9DLzDMw7DA8hzxQiSiF7rU7vEQMqIyaBJzS7IRsaxzJkfrj1DCmEWQbynjw49w0Aksp4Q8pTP_wYtWAX5NaiMr39CvQ4B6XtcEJf7BIU4zCNdqXcKnN2vQuOvzgHe2VGz7seTeceyZ1WxuHTtW_J5-7toziE1XFfFnkVtizhS8gZ19iITrcqAZpkMdfAY9ZqlNq_ioIr3aUomcAUBdVNLBpIWgQQ2CiZ8i2By912Hp2bUdfT3A9qPtcU6lVF7VXUq4r6qsJHXi6RHhH_1yWTScZS_gek_lse</recordid><startdate>201804</startdate><enddate>201804</enddate><creator>Silva, Daniel G.</creator><creator>Attux, Romis</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-2858-1110</orcidid></search><sort><creationdate>201804</creationdate><title>Simulated Annealing for Independent Component Analysis Over Galois Fields</title><author>Silva, Daniel G. ; Attux, Romis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithm design and analysis</topic><topic>Combinatorial optimization</topic><topic>Correlation</topic><topic>Cost function</topic><topic>Entropy</topic><topic>finite fields</topic><topic>Independent Component Analysis (ICA)</topic><topic>Signal processing algorithms</topic><topic>Simulated annealing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Silva, Daniel G.</creatorcontrib><creatorcontrib>Attux, Romis</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><jtitle>IEEE signal processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Silva, Daniel G.</au><au>Attux, Romis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulated Annealing for Independent Component Analysis Over Galois Fields</atitle><jtitle>IEEE signal processing letters</jtitle><stitle>LSP</stitle><date>2018-04</date><risdate>2018</risdate><volume>25</volume><issue>4</issue><spage>516</spage><epage>520</epage><pages>516-520</pages><issn>1070-9908</issn><eissn>1558-2361</eissn><coden>ISPLEM</coden><abstract>Independent Component Analysis over finite fields is an unsupervised signal processing problem that poses a challenging combinatorial optimization task. In this context, a solution based on Simulated Annealing, with an entropy-based objective function, is proposed. The empirical results demonstrate the effectiveness of the method, with a performance competitive or superior to that of the reference techniques, at an inferior asymptotic computational cost.</abstract><pub>IEEE</pub><doi>10.1109/LSP.2018.2803619</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0003-2858-1110</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1070-9908
ispartof IEEE signal processing letters, 2018-04, Vol.25 (4), p.516-520
issn 1070-9908
1558-2361
language eng
recordid cdi_ieee_primary_8286927
source IEEE Electronic Library (IEL) Journals
subjects Algorithm design and analysis
Combinatorial optimization
Correlation
Cost function
Entropy
finite fields
Independent Component Analysis (ICA)
Signal processing algorithms
Simulated annealing
title Simulated Annealing for Independent Component Analysis Over Galois Fields
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T13%3A17%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Simulated%20Annealing%20for%20Independent%20Component%20Analysis%20Over%20Galois%20Fields&rft.jtitle=IEEE%20signal%20processing%20letters&rft.au=Silva,%20Daniel%20G.&rft.date=2018-04&rft.volume=25&rft.issue=4&rft.spage=516&rft.epage=520&rft.pages=516-520&rft.issn=1070-9908&rft.eissn=1558-2361&rft.coden=ISPLEM&rft_id=info:doi/10.1109/LSP.2018.2803619&rft_dat=%3Ccrossref_ieee_%3E10_1109_LSP_2018_2803619%3C/crossref_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c263t-323feb4dfca6016953f0352cfe8f361e43afd7e824e7e41fb54b06ce004eba873%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=8286927&rfr_iscdi=true