Vectorization of the DLMS transversal adaptive filter
The subject of high sampling rate realizations for transversal adaptive filters is addressed. In particular, a vectorized version of the delayed least mean squares (DLMS) algorithm is derived using look-ahead computation techniques. The resulting parallel algorithm is then mapped onto a linear array...
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Veröffentlicht in: | IEEE transactions on signal processing 1994-11, Vol.42 (11), p.3237-3240 |
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container_title | IEEE transactions on signal processing |
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creator | Meyer, M.D. Agrawal, D.P. |
description | The subject of high sampling rate realizations for transversal adaptive filters is addressed. In particular, a vectorized version of the delayed least mean squares (DLMS) algorithm is derived using look-ahead computation techniques. The resulting parallel algorithm is then mapped onto a linear array of highly pipelined processing modules, which can accept an input vector of arbitrary length, and compute the corresponding output vector in a single clock cycle. The proposed system is shown to be capable of implementing transversal adaptive filters at sampling rates which are theoretically without bound. The performance of the proposed system is analyzed and simulation results are presented to verify the convergence properties of the algorithm under varying degrees of vectorization.< > |
doi_str_mv | 10.1109/78.330384 |
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In particular, a vectorized version of the delayed least mean squares (DLMS) algorithm is derived using look-ahead computation techniques. The resulting parallel algorithm is then mapped onto a linear array of highly pipelined processing modules, which can accept an input vector of arbitrary length, and compute the corresponding output vector in a single clock cycle. The proposed system is shown to be capable of implementing transversal adaptive filters at sampling rates which are theoretically without bound. The performance of the proposed system is analyzed and simulation results are presented to verify the convergence properties of the algorithm under varying degrees of vectorization.< ></description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/78.330384</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Adaptive filters ; Algorithm design and analysis ; Applied sciences ; Clocks ; Computational modeling ; Concurrent computing ; Delay ; Detection, estimation, filtering, equalization, prediction ; Exact sciences and technology ; Information, signal and communications theory ; Parallel algorithms ; Performance analysis ; Sampling methods ; Signal and communications theory ; Signal, noise ; Telecommunications and information theory ; Vectors</subject><ispartof>IEEE transactions on signal processing, 1994-11, Vol.42 (11), p.3237-3240</ispartof><rights>1995 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-7a0bed70b42446e3da36a72e35e262fe0a3d7dd025b7c2f1d54dff36129358e93</citedby><cites>FETCH-LOGICAL-c337t-7a0bed70b42446e3da36a72e35e262fe0a3d7dd025b7c2f1d54dff36129358e93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/330384$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/330384$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3376696$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Meyer, M.D.</creatorcontrib><creatorcontrib>Agrawal, D.P.</creatorcontrib><title>Vectorization of the DLMS transversal adaptive filter</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>The subject of high sampling rate realizations for transversal adaptive filters is addressed. 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The performance of the proposed system is analyzed and simulation results are presented to verify the convergence properties of the algorithm under varying degrees of vectorization.< ></description><subject>Adaptive filters</subject><subject>Algorithm design and analysis</subject><subject>Applied sciences</subject><subject>Clocks</subject><subject>Computational modeling</subject><subject>Concurrent computing</subject><subject>Delay</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>Information, signal and communications theory</subject><subject>Parallel algorithms</subject><subject>Performance analysis</subject><subject>Sampling methods</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>Telecommunications and information theory</subject><subject>Vectors</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1994</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQhoMoWKsHr572IIKHrUkmH5uj1E-oePADb0u6mWBk261JWtBf72qLePM0A_PMC-9DyCGjI8aoOdPVCIBCJbbIgBnBSiq02u53KqGUlX7ZJXspvVHKhDBqQOQzNrmL4dPm0M2Lzhf5FYuLyd1DkaOdpxXGZNvCOrvIYYWFD23GuE92vG0THmzmkDxdXT6Ob8rJ_fXt-HxSNgA6l9rSKTpNp4ILoRCcBWU1R5DIFfdILTjtHOVyqhvumZPCeQ-KcQOyQgNDcrLOXcTufYkp17OQGmxbO8dumWpeaejryv9BzY1hBnrwdA02sUspoq8XMcxs_KgZrb8N1rqq1wZ79ngTalNjW9_7aEL6fegrKmVUjx2tsYCIf64_GV_hxXbq</recordid><startdate>19941101</startdate><enddate>19941101</enddate><creator>Meyer, M.D.</creator><creator>Agrawal, D.P.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</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></search><sort><creationdate>19941101</creationdate><title>Vectorization of the DLMS transversal adaptive filter</title><author>Meyer, M.D. ; Agrawal, D.P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-7a0bed70b42446e3da36a72e35e262fe0a3d7dd025b7c2f1d54dff36129358e93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Adaptive filters</topic><topic>Algorithm design and analysis</topic><topic>Applied sciences</topic><topic>Clocks</topic><topic>Computational modeling</topic><topic>Concurrent computing</topic><topic>Delay</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Exact sciences and technology</topic><topic>Information, signal and communications theory</topic><topic>Parallel algorithms</topic><topic>Performance analysis</topic><topic>Sampling methods</topic><topic>Signal and communications theory</topic><topic>Signal, noise</topic><topic>Telecommunications and information theory</topic><topic>Vectors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Meyer, M.D.</creatorcontrib><creatorcontrib>Agrawal, D.P.</creatorcontrib><collection>Pascal-Francis</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><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Meyer, M.D.</au><au>Agrawal, D.P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Vectorization of the DLMS transversal adaptive filter</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>1994-11-01</date><risdate>1994</risdate><volume>42</volume><issue>11</issue><spage>3237</spage><epage>3240</epage><pages>3237-3240</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>The subject of high sampling rate realizations for transversal adaptive filters is addressed. 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subjects | Adaptive filters Algorithm design and analysis Applied sciences Clocks Computational modeling Concurrent computing Delay Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Parallel algorithms Performance analysis Sampling methods Signal and communications theory Signal, noise Telecommunications and information theory Vectors |
title | Vectorization of the DLMS transversal adaptive filter |
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