Comparison of the convergence of two algorithms for adaptive FIR digital filters
The convergence properties of two different algorithms for the updating of the coefficients of an adaptive FIR digital filter are investigated and compared with one another. These algorithms are the stochastic iteration algorithm and the sign algorithm. In this latter algorithm a one-bit gradient es...
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| Veröffentlicht in: | IEEE transactions on circuits and systems 1981-06, Vol.28 (6), p.510-518 |
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| container_end_page | 518 |
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| container_issue | 6 |
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| container_title | IEEE transactions on circuits and systems |
| container_volume | 28 |
| creator | Claasen, T. Mecklenbrauker, W. |
| description | The convergence properties of two different algorithms for the updating of the coefficients of an adaptive FIR digital filter are investigated and compared with one another. These algorithms are the stochastic iteration algorithm and the sign algorithm. In this latter algorithm a one-bit gradient estimation is used which makes its implementation very simple. The convergence is characterized by the residual echo variance after convergence, and a parameter that indicates the speed of the convergence. It is shown that the convergence of the sign algorithm can always be assured but is much slower than that of the stochastic iteration algorithm if the same variance of the residual echo is to be obtained. |
| doi_str_mv | 10.1109/TCS.1981.1085011 |
| format | Article |
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These algorithms are the stochastic iteration algorithm and the sign algorithm. In this latter algorithm a one-bit gradient estimation is used which makes its implementation very simple. The convergence is characterized by the residual echo variance after convergence, and a parameter that indicates the speed of the convergence. It is shown that the convergence of the sign algorithm can always be assured but is much slower than that of the stochastic iteration algorithm if the same variance of the residual echo is to be obtained.</description><identifier>ISSN: 0098-4094</identifier><identifier>EISSN: 1558-1276</identifier><identifier>DOI: 10.1109/TCS.1981.1085011</identifier><identifier>CODEN: ICSYBT</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive signal processing ; Australia ; Convergence ; Digital filters ; Echo cancellers ; Electrical engineering ; Finite impulse response filter ; Optimal control ; Signal processing algorithms ; Stochastic processes</subject><ispartof>IEEE transactions on circuits and systems, 1981-06, Vol.28 (6), p.510-518</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c242t-6c5e58aa9c8f0733906dcfb69a85bd94a607029783f19bf8c6a6c8db472f28cb3</citedby><cites>FETCH-LOGICAL-c242t-6c5e58aa9c8f0733906dcfb69a85bd94a607029783f19bf8c6a6c8db472f28cb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1085011$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1085011$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Claasen, T.</creatorcontrib><creatorcontrib>Mecklenbrauker, W.</creatorcontrib><title>Comparison of the convergence of two algorithms for adaptive FIR digital filters</title><title>IEEE transactions on circuits and systems</title><addtitle>T-CAS</addtitle><description>The convergence properties of two different algorithms for the updating of the coefficients of an adaptive FIR digital filter are investigated and compared with one another. These algorithms are the stochastic iteration algorithm and the sign algorithm. In this latter algorithm a one-bit gradient estimation is used which makes its implementation very simple. The convergence is characterized by the residual echo variance after convergence, and a parameter that indicates the speed of the convergence. It is shown that the convergence of the sign algorithm can always be assured but is much slower than that of the stochastic iteration algorithm if the same variance of the residual echo is to be obtained.</description><subject>Adaptive signal processing</subject><subject>Australia</subject><subject>Convergence</subject><subject>Digital filters</subject><subject>Echo cancellers</subject><subject>Electrical engineering</subject><subject>Finite impulse response filter</subject><subject>Optimal control</subject><subject>Signal processing algorithms</subject><subject>Stochastic processes</subject><issn>0098-4094</issn><issn>1558-1276</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1981</creationdate><recordtype>article</recordtype><recordid>eNpNkE1LwzAYx4MoWKd3wUu-QOuTvqRPjlKcGwwUneeSpkkXaZuSlInf3s3t4OkP_7fDj5B7BgljIB631UfCBLKEARbA2AWJWFFgzNKSX5IIQGCcg8ivyU0IXwCAAjEib5UbJultcCN1hs47TZUb99p3elT6z_p2VPad83beDYEa56ls5TTbvabL9TttbWdn2VNj-1n7cEuujOyDvjvrgnwun7fVKt68vqyrp02s0jydY64KXaCUQqGBMssE8FaZhguJRdOKXHIoIRUlZoaJxqDikitsm7xMTYqqyRYETr_KuxC8NvXk7SD9T82gPhKpD0TqI5H6TOQweThNrNb6X_2U_gKVFV1t</recordid><startdate>198106</startdate><enddate>198106</enddate><creator>Claasen, T.</creator><creator>Mecklenbrauker, W.</creator><general>IEEE</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>198106</creationdate><title>Comparison of the convergence of two algorithms for adaptive FIR digital filters</title><author>Claasen, T. ; Mecklenbrauker, W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c242t-6c5e58aa9c8f0733906dcfb69a85bd94a607029783f19bf8c6a6c8db472f28cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1981</creationdate><topic>Adaptive signal processing</topic><topic>Australia</topic><topic>Convergence</topic><topic>Digital filters</topic><topic>Echo cancellers</topic><topic>Electrical engineering</topic><topic>Finite impulse response filter</topic><topic>Optimal control</topic><topic>Signal processing algorithms</topic><topic>Stochastic processes</topic><toplevel>online_resources</toplevel><creatorcontrib>Claasen, T.</creatorcontrib><creatorcontrib>Mecklenbrauker, W.</creatorcontrib><collection>CrossRef</collection><jtitle>IEEE transactions on circuits and systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Claasen, T.</au><au>Mecklenbrauker, W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of the convergence of two algorithms for adaptive FIR digital filters</atitle><jtitle>IEEE transactions on circuits and systems</jtitle><stitle>T-CAS</stitle><date>1981-06</date><risdate>1981</risdate><volume>28</volume><issue>6</issue><spage>510</spage><epage>518</epage><pages>510-518</pages><issn>0098-4094</issn><eissn>1558-1276</eissn><coden>ICSYBT</coden><abstract>The convergence properties of two different algorithms for the updating of the coefficients of an adaptive FIR digital filter are investigated and compared with one another. These algorithms are the stochastic iteration algorithm and the sign algorithm. In this latter algorithm a one-bit gradient estimation is used which makes its implementation very simple. The convergence is characterized by the residual echo variance after convergence, and a parameter that indicates the speed of the convergence. It is shown that the convergence of the sign algorithm can always be assured but is much slower than that of the stochastic iteration algorithm if the same variance of the residual echo is to be obtained.</abstract><pub>IEEE</pub><doi>10.1109/TCS.1981.1085011</doi><tpages>9</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive signal processing Australia Convergence Digital filters Echo cancellers Electrical engineering Finite impulse response filter Optimal control Signal processing algorithms Stochastic processes |
| title | Comparison of the convergence of two algorithms for adaptive FIR digital filters |
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