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A PNLMS Algorithm With Individual Activation Factors
This paper presents a proportionate normalized least-mean-square (PNLMS) algorithm using individual activation factors for each adaptive filter coefficient, instead of a global activation factor as in the standard PNLMS algorithm. The proposed individual activation factors, determined in terms of th...
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| Published in: | IEEE transactions on signal processing 2010-04, Vol.58 (4), p.2036-2047 |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
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| cites | cdi_FETCH-LOGICAL-c354t-85ed26f56c2956017c7e3d6a0979d737636a27b6fe5e48cb21ecd24f472813e13 |
| container_end_page | 2047 |
| container_issue | 4 |
| container_start_page | 2036 |
| container_title | IEEE transactions on signal processing |
| container_volume | 58 |
| creator | das Chagas de Souza, F. Tobias, O.J. Seara, R. Morgan, D.R. |
| description | This paper presents a proportionate normalized least-mean-square (PNLMS) algorithm using individual activation factors for each adaptive filter coefficient, instead of a global activation factor as in the standard PNLMS algorithm. The proposed individual activation factors, determined in terms of the corresponding adaptive filter coefficients, are recursively updated. This approach leads to a better distribution of the adaptation energy over the filter coefficients than the standard PNLMS does. Thereby, for impulse responses exhibiting high sparseness, the proposed algorithm achieves faster convergence, outperforming both the PNLMS and improved PNLMS (IPNLMS) algorithms. |
| doi_str_mv | 10.1109/TSP.2009.2038420 |
| format | article |
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The proposed individual activation factors, determined in terms of the corresponding adaptive filter coefficients, are recursively updated. This approach leads to a better distribution of the adaptation energy over the filter coefficients than the standard PNLMS does. Thereby, for impulse responses exhibiting high sparseness, the proposed algorithm achieves faster convergence, outperforming both the PNLMS and improved PNLMS (IPNLMS) algorithms.</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2009.2038420</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Acoustic applications ; Activation ; Adaptation ; Adaptive filtering ; Adaptive filters ; Algorithms ; Applied sciences ; Chemical processes ; Coefficients ; Convergence ; Detection, estimation, filtering, equalization, prediction ; Encoding ; Energy distribution ; Exact sciences and technology ; Filtering algorithms ; Information, signal and communications theory ; Miscellaneous ; Packet switching ; Propagation delay ; proportionate normalized least-mean-square (PNLMS) algorithm ; Signal and communications theory ; Signal processing ; Signal processing algorithms ; Signal, noise ; sparse impulse response ; sparse system identification ; System identification ; Telecommunications and information theory</subject><ispartof>IEEE transactions on signal processing, 2010-04, Vol.58 (4), p.2036-2047</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Apr 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c354t-85ed26f56c2956017c7e3d6a0979d737636a27b6fe5e48cb21ecd24f472813e13</citedby><cites>FETCH-LOGICAL-c354t-85ed26f56c2956017c7e3d6a0979d737636a27b6fe5e48cb21ecd24f472813e13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5352326$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22728853$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>das Chagas de Souza, F.</creatorcontrib><creatorcontrib>Tobias, O.J.</creatorcontrib><creatorcontrib>Seara, R.</creatorcontrib><creatorcontrib>Morgan, D.R.</creatorcontrib><title>A PNLMS Algorithm With Individual Activation Factors</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>This paper presents a proportionate normalized least-mean-square (PNLMS) algorithm using individual activation factors for each adaptive filter coefficient, instead of a global activation factor as in the standard PNLMS algorithm. The proposed individual activation factors, determined in terms of the corresponding adaptive filter coefficients, are recursively updated. This approach leads to a better distribution of the adaptation energy over the filter coefficients than the standard PNLMS does. Thereby, for impulse responses exhibiting high sparseness, the proposed algorithm achieves faster convergence, outperforming both the PNLMS and improved PNLMS (IPNLMS) algorithms.</description><subject>Acoustic applications</subject><subject>Activation</subject><subject>Adaptation</subject><subject>Adaptive filtering</subject><subject>Adaptive filters</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Chemical processes</subject><subject>Coefficients</subject><subject>Convergence</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Encoding</subject><subject>Energy distribution</subject><subject>Exact sciences and technology</subject><subject>Filtering algorithms</subject><subject>Information, signal and communications theory</subject><subject>Miscellaneous</subject><subject>Packet switching</subject><subject>Propagation delay</subject><subject>proportionate normalized least-mean-square (PNLMS) algorithm</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal processing algorithms</subject><subject>Signal, noise</subject><subject>sparse impulse response</subject><subject>sparse system identification</subject><subject>System identification</subject><subject>Telecommunications and information theory</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNpd0M9LwzAUB_AgCs7pXfBSEMFLZ36nOZbhdDB1sIneQpammtG1M2kH_vdmrOzg5SWQz3svfAG4RnCEEJQPy8V8hCGUsZCMYngCBkhSlEIq-Gm8Q0ZSlonPc3ARwhpCRKnkA0DzZP46e1kkefXVeNd-b5KPWJNpXbidKzpdJblp3U63rqmTiTZt48MlOCt1FexVfw7B--RxOX5OZ29P03E-Sw1htE0zZgvMS8YNloxDJIywpOAaSiELQQQnXGOx4qVllmZmhZE1BaYlFThDxCIyBPeHuVvf_HQ2tGrjgrFVpWvbdEEhLhAhIvJIb__RddP5Ov5OIYgj44KJqOBBGd-E4G2ptt5ttP-NSO1jVDFGtY9R9THGlrt-sA5GV6XXtXHh2Idx3J4xEt3NwTlr7fGZEYYJ5uQPbkh3yg</recordid><startdate>20100401</startdate><enddate>20100401</enddate><creator>das Chagas de Souza, F.</creator><creator>Tobias, O.J.</creator><creator>Seara, R.</creator><creator>Morgan, D.R.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The proposed individual activation factors, determined in terms of the corresponding adaptive filter coefficients, are recursively updated. This approach leads to a better distribution of the adaptation energy over the filter coefficients than the standard PNLMS does. Thereby, for impulse responses exhibiting high sparseness, the proposed algorithm achieves faster convergence, outperforming both the PNLMS and improved PNLMS (IPNLMS) algorithms.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TSP.2009.2038420</doi><tpages>12</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1053-587X |
| ispartof | IEEE transactions on signal processing, 2010-04, Vol.58 (4), p.2036-2047 |
| issn | 1053-587X 1941-0476 |
| language | eng |
| recordid | cdi_ieee_primary_5352326 |
| source | IEEE Electronic Library (IEL) Journals |
| subjects | Acoustic applications Activation Adaptation Adaptive filtering Adaptive filters Algorithms Applied sciences Chemical processes Coefficients Convergence Detection, estimation, filtering, equalization, prediction Encoding Energy distribution Exact sciences and technology Filtering algorithms Information, signal and communications theory Miscellaneous Packet switching Propagation delay proportionate normalized least-mean-square (PNLMS) algorithm Signal and communications theory Signal processing Signal processing algorithms Signal, noise sparse impulse response sparse system identification System identification Telecommunications and information theory |
| title | A PNLMS Algorithm With Individual Activation Factors |
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