FIR–IIR adaptive filters hybrid combination
To enhance the performance in IIR system identification scenarios, a hybrid combination of FIR and IIR adaptive filters (AFs) via a supervisor that senses which one is performing best is proposed. The FIR-LMS AF is short, providing fast and robust convergence, whereas the IIR-LMS AF is slow but accu...
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| Veröffentlicht in: | Electronics letters 2014-03, Vol.50 (7), p.501-503 |
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| container_end_page | 503 |
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| container_issue | 7 |
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| container_title | Electronics letters |
| container_volume | 50 |
| creator | Ferro, H.F Chamon, L.F.O Lopes, C.G |
| description | To enhance the performance in IIR system identification scenarios, a hybrid combination of FIR and IIR adaptive filters (AFs) via a supervisor that senses which one is performing best is proposed. The FIR-LMS AF is short, providing fast and robust convergence, whereas the IIR-LMS AF is slow but accurate. The stagnation effect caused by the different convergence rates is tackled through cyclic weight transfers FIR → IIR, which also ensure good tracking properties. A design technique for the transfers cycle length is proposed, providing good convergence while keeping computational cost low. |
| doi_str_mv | 10.1049/el.2014.0248 |
| format | Article |
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The FIR-LMS AF is short, providing fast and robust convergence, whereas the IIR-LMS AF is slow but accurate. The stagnation effect caused by the different convergence rates is tackled through cyclic weight transfers FIR → IIR, which also ensure good tracking properties. A design technique for the transfers cycle length is proposed, providing good convergence while keeping computational cost low.</description><identifier>ISSN: 0013-5194</identifier><identifier>ISSN: 1350-911X</identifier><identifier>EISSN: 1350-911X</identifier><identifier>DOI: 10.1049/el.2014.0248</identifier><identifier>CODEN: ELLEAK</identifier><language>eng</language><publisher>Stevenage: The Institution of Engineering and Technology</publisher><subject>adaptive filters ; Applied sciences ; Circuits and systems ; convergence ; cyclic weight transfer ; Detection, estimation, filtering, equalization, prediction ; Exact sciences and technology ; FIR filters ; FIR‐LMS AF ; hybrid FIR‐IIR adaptive filter combination ; identification ; IIR filters ; IIR system identification ; IIR‐LMS AF ; Information, signal and communications theory ; least mean squares methods ; Signal and communications theory ; Signal, noise ; stagnation effect ; supervisor ; Telecommunications and information theory</subject><ispartof>Electronics letters, 2014-03, Vol.50 (7), p.501-503</ispartof><rights>The Institution of Engineering and Technology</rights><rights>2020 The Institution of Engineering and Technology</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4117-5d172532e8c9905a6e378535f67dbb2d5b8fc4c70e0c2807c5aa97a8169cbcf43</citedby><cites>FETCH-LOGICAL-c4117-5d172532e8c9905a6e378535f67dbb2d5b8fc4c70e0c2807c5aa97a8169cbcf43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1049%2Fel.2014.0248$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1049%2Fel.2014.0248$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,11541,27901,27902,45550,45551,46027,46451</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1049%2Fel.2014.0248$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28535495$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Ferro, H.F</creatorcontrib><creatorcontrib>Chamon, L.F.O</creatorcontrib><creatorcontrib>Lopes, C.G</creatorcontrib><title>FIR–IIR adaptive filters hybrid combination</title><title>Electronics letters</title><description>To enhance the performance in IIR system identification scenarios, a hybrid combination of FIR and IIR adaptive filters (AFs) via a supervisor that senses which one is performing best is proposed. 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A design technique for the transfers cycle length is proposed, providing good convergence while keeping computational cost low.</description><subject>adaptive filters</subject><subject>Applied sciences</subject><subject>Circuits and systems</subject><subject>convergence</subject><subject>cyclic weight transfer</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>FIR filters</subject><subject>FIR‐LMS AF</subject><subject>hybrid FIR‐IIR adaptive filter combination</subject><subject>identification</subject><subject>IIR filters</subject><subject>IIR system identification</subject><subject>IIR‐LMS AF</subject><subject>Information, signal and communications theory</subject><subject>least mean squares methods</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>stagnation effect</subject><subject>supervisor</subject><subject>Telecommunications and information theory</subject><issn>0013-5194</issn><issn>1350-911X</issn><issn>1350-911X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kMFKxDAQhoMouKx78wF6UPBg10yaNM1Rl10tFIRFwVtI0wQj3bYkq7I338E39ElsqYgH9TSX7_9nvkHoGPAcMBUXpp4TDHSOCc320AQShmMB8LCPJhhDEjMQ9BDNQnBljwFNMYUJilf5-uPtPc_XkapUt3UvJrKu3hofosdd6V0V6XZTukZtXdscoQOr6mBmX3OK7lfLu8VNXNxe54vLItYUgMesAk5YQkymhcBMpSbhGUuYTXlVlqRiZWY11RwbrEmGuWZKCa4ySIUutaXJFJ2Pvdq3IXhjZefdRvmdBCwHW2lqOdjKwbbHT0e8U0Gr2nrVaBe-M2TYTQXrOTZyr642u3875bIoyNWqfxzmfe5szDmzlU_ts296-b9OOfkFXRY_mrvKJp-8W3xN</recordid><startdate>20140327</startdate><enddate>20140327</enddate><creator>Ferro, H.F</creator><creator>Chamon, L.F.O</creator><creator>Lopes, C.G</creator><general>The Institution of Engineering and Technology</general><general>Institution of Engineering and Technology</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20140327</creationdate><title>FIR–IIR adaptive filters hybrid combination</title><author>Ferro, H.F ; Chamon, L.F.O ; Lopes, C.G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4117-5d172532e8c9905a6e378535f67dbb2d5b8fc4c70e0c2807c5aa97a8169cbcf43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>adaptive filters</topic><topic>Applied sciences</topic><topic>Circuits and systems</topic><topic>convergence</topic><topic>cyclic weight transfer</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Exact sciences and technology</topic><topic>FIR filters</topic><topic>FIR‐LMS AF</topic><topic>hybrid FIR‐IIR adaptive filter combination</topic><topic>identification</topic><topic>IIR filters</topic><topic>IIR system identification</topic><topic>IIR‐LMS AF</topic><topic>Information, signal and communications theory</topic><topic>least mean squares methods</topic><topic>Signal and communications theory</topic><topic>Signal, noise</topic><topic>stagnation effect</topic><topic>supervisor</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ferro, H.F</creatorcontrib><creatorcontrib>Chamon, L.F.O</creatorcontrib><creatorcontrib>Lopes, C.G</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Electronics letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ferro, H.F</au><au>Chamon, L.F.O</au><au>Lopes, C.G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>FIR–IIR adaptive filters hybrid combination</atitle><jtitle>Electronics letters</jtitle><date>2014-03-27</date><risdate>2014</risdate><volume>50</volume><issue>7</issue><spage>501</spage><epage>503</epage><pages>501-503</pages><issn>0013-5194</issn><issn>1350-911X</issn><eissn>1350-911X</eissn><coden>ELLEAK</coden><abstract>To enhance the performance in IIR system identification scenarios, a hybrid combination of FIR and IIR adaptive filters (AFs) via a supervisor that senses which one is performing best is proposed. The FIR-LMS AF is short, providing fast and robust convergence, whereas the IIR-LMS AF is slow but accurate. The stagnation effect caused by the different convergence rates is tackled through cyclic weight transfers FIR → IIR, which also ensure good tracking properties. A design technique for the transfers cycle length is proposed, providing good convergence while keeping computational cost low.</abstract><cop>Stevenage</cop><pub>The Institution of Engineering and Technology</pub><doi>10.1049/el.2014.0248</doi><tpages>3</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Electronics letters, 2014-03, Vol.50 (7), p.501-503 |
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| subjects | adaptive filters Applied sciences Circuits and systems convergence cyclic weight transfer Detection, estimation, filtering, equalization, prediction Exact sciences and technology FIR filters FIR‐LMS AF hybrid FIR‐IIR adaptive filter combination identification IIR filters IIR system identification IIR‐LMS AF Information, signal and communications theory least mean squares methods Signal and communications theory Signal, noise stagnation effect supervisor Telecommunications and information theory |
| title | FIR–IIR adaptive filters hybrid combination |
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