Online adaptive blind deconvolution based on third-order moments
Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric...
Gespeichert in:
| Veröffentlicht in: | IEEE signal processing letters 2005-12, Vol.12 (12), p.863-866 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 866 |
|---|---|
| container_issue | 12 |
| container_start_page | 863 |
| container_title | IEEE signal processing letters |
| container_volume | 12 |
| creator | Paajarvi, P. LeBlanc, J.P. |
| description | Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel. |
| doi_str_mv | 10.1109/LSP.2005.859496 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_LSP_2005_859496</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1542119</ieee_id><sourcerecordid>2425090331</sourcerecordid><originalsourceid>FETCH-LOGICAL-c366t-abad5dbfa7faab9d563f9c9f7d24f3c5fb0c11977bb6efed5fe728ef45ef655d3</originalsourceid><addsrcrecordid>eNpFkM1LxDAUxIMouK6ePXgpnu1u0jRtcnNZP2FhBT-uIWletEu3qUm74n9vloqe3jz4zTAMQucEzwjBYr56fpplGLMZZyIXxQGaEMZ4mtGCHEaNS5wKgfkxOglhgzHmhLMJul63Td1Coozq-noHiY6vSQxUrt25Zuhr1yZaBTBJFP1H7U3qvAGfbN0W2j6coiOrmgBnv3eKXu9uX5YP6Wp9_7hcrNKKFkWfKq0MM9qq0iqlhWEFtaIStjRZbmnFrMYVIaIstS7AgmEWyoyDzRnYgjFDp-hqzA1f0A1adr7eKv8tnarlTf22kM6_y6YfJMEsExG_HPHOu88BQi83bvBtbCg5p5TzXLAIzUeo8i4ED_YvlWC5H1XGUeV-VDmOGh0Xo6MGgH-a5VksT38Adgp1CA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>883388495</pqid></control><display><type>article</type><title>Online adaptive blind deconvolution based on third-order moments</title><source>IEEE Electronic Library (IEL)</source><creator>Paajarvi, P. ; LeBlanc, J.P.</creator><creatorcontrib>Paajarvi, P. ; LeBlanc, J.P.</creatorcontrib><description>Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel.</description><identifier>ISSN: 1070-9908</identifier><identifier>ISSN: 1558-2361</identifier><identifier>EISSN: 1558-2361</identifier><identifier>DOI: 10.1109/LSP.2005.859496</identifier><identifier>CODEN: ISPLEM</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adaptive filtering ; blind equalization ; Blind equalizers ; Communication channels ; Convergence ; Deconvolution ; Entropy ; Finite impulse response filter ; Gaussian processes ; Probability density function ; Probability distribution ; Signal Processing ; Signalbehandling ; third-order moments ; Ultra wideband technology</subject><ispartof>IEEE signal processing letters, 2005-12, Vol.12 (12), p.863-866</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2005</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-abad5dbfa7faab9d563f9c9f7d24f3c5fb0c11977bb6efed5fe728ef45ef655d3</citedby><cites>FETCH-LOGICAL-c366t-abad5dbfa7faab9d563f9c9f7d24f3c5fb0c11977bb6efed5fe728ef45ef655d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1542119$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,550,776,780,792,881,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1542119$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-10529$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Paajarvi, P.</creatorcontrib><creatorcontrib>LeBlanc, J.P.</creatorcontrib><title>Online adaptive blind deconvolution based on third-order moments</title><title>IEEE signal processing letters</title><addtitle>LSP</addtitle><description>Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel.</description><subject>Adaptive filtering</subject><subject>blind equalization</subject><subject>Blind equalizers</subject><subject>Communication channels</subject><subject>Convergence</subject><subject>Deconvolution</subject><subject>Entropy</subject><subject>Finite impulse response filter</subject><subject>Gaussian processes</subject><subject>Probability density function</subject><subject>Probability distribution</subject><subject>Signal Processing</subject><subject>Signalbehandling</subject><subject>third-order moments</subject><subject>Ultra wideband technology</subject><issn>1070-9908</issn><issn>1558-2361</issn><issn>1558-2361</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>D8T</sourceid><recordid>eNpFkM1LxDAUxIMouK6ePXgpnu1u0jRtcnNZP2FhBT-uIWletEu3qUm74n9vloqe3jz4zTAMQucEzwjBYr56fpplGLMZZyIXxQGaEMZ4mtGCHEaNS5wKgfkxOglhgzHmhLMJul63Td1Coozq-noHiY6vSQxUrt25Zuhr1yZaBTBJFP1H7U3qvAGfbN0W2j6coiOrmgBnv3eKXu9uX5YP6Wp9_7hcrNKKFkWfKq0MM9qq0iqlhWEFtaIStjRZbmnFrMYVIaIstS7AgmEWyoyDzRnYgjFDp-hqzA1f0A1adr7eKv8tnarlTf22kM6_y6YfJMEsExG_HPHOu88BQi83bvBtbCg5p5TzXLAIzUeo8i4ED_YvlWC5H1XGUeV-VDmOGh0Xo6MGgH-a5VksT38Adgp1CA</recordid><startdate>20051201</startdate><enddate>20051201</enddate><creator>Paajarvi, P.</creator><creator>LeBlanc, J.P.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>ZZAVC</scope></search><sort><creationdate>20051201</creationdate><title>Online adaptive blind deconvolution based on third-order moments</title><author>Paajarvi, P. ; LeBlanc, J.P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-abad5dbfa7faab9d563f9c9f7d24f3c5fb0c11977bb6efed5fe728ef45ef655d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adaptive filtering</topic><topic>blind equalization</topic><topic>Blind equalizers</topic><topic>Communication channels</topic><topic>Convergence</topic><topic>Deconvolution</topic><topic>Entropy</topic><topic>Finite impulse response filter</topic><topic>Gaussian processes</topic><topic>Probability density function</topic><topic>Probability distribution</topic><topic>Signal Processing</topic><topic>Signalbehandling</topic><topic>third-order moments</topic><topic>Ultra wideband technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Paajarvi, P.</creatorcontrib><creatorcontrib>LeBlanc, J.P.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SwePub Articles full text</collection><jtitle>IEEE signal processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Paajarvi, P.</au><au>LeBlanc, J.P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Online adaptive blind deconvolution based on third-order moments</atitle><jtitle>IEEE signal processing letters</jtitle><stitle>LSP</stitle><date>2005-12-01</date><risdate>2005</risdate><volume>12</volume><issue>12</issue><spage>863</spage><epage>866</epage><pages>863-866</pages><issn>1070-9908</issn><issn>1558-2361</issn><eissn>1558-2361</eissn><coden>ISPLEM</coden><abstract>Traditional methods for online adaptive blind deconvolution using higher order statistics are often based on even-order moments, due to the fact that the systems considered commonly feature symmetric source signals (i.e., signals having a symmetric probability density function). However, asymmetric source signals facilitate blind deconvolution based on odd-order moments. In this letter, we show that third-order moments give the benefits of faster convergence of algorithms and increased robustness to additive Gaussian noise. The convergence rates for two algorithms based on third- and fourth-order moments, respectively, are compared for a simulated ultra-wideband communication channel.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/LSP.2005.859496</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1070-9908 |
| ispartof | IEEE signal processing letters, 2005-12, Vol.12 (12), p.863-866 |
| issn | 1070-9908 1558-2361 1558-2361 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_LSP_2005_859496 |
| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive filtering blind equalization Blind equalizers Communication channels Convergence Deconvolution Entropy Finite impulse response filter Gaussian processes Probability density function Probability distribution Signal Processing Signalbehandling third-order moments Ultra wideband technology |
| title | Online adaptive blind deconvolution based on third-order moments |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T04%3A45%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Online%20adaptive%20blind%20deconvolution%20based%20on%20third-order%20moments&rft.jtitle=IEEE%20signal%20processing%20letters&rft.au=Paajarvi,%20P.&rft.date=2005-12-01&rft.volume=12&rft.issue=12&rft.spage=863&rft.epage=866&rft.pages=863-866&rft.issn=1070-9908&rft.eissn=1558-2361&rft.coden=ISPLEM&rft_id=info:doi/10.1109/LSP.2005.859496&rft_dat=%3Cproquest_RIE%3E2425090331%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=883388495&rft_id=info:pmid/&rft_ieee_id=1542119&rfr_iscdi=true |