Efficient System Tracking With Decomposable Graph-Structured Inputs and Application to Adaptive Equalization With Cyclostationary Inputs
This paper introduces the graph-structured recursive least squares (GS-RLS) algorithm, which is a very efficient means to track a linear time-varying system when the inputs to the system have structure that can be modeled using a decomposable Gaussian graphical model. For graphs with small clique si...
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| Veröffentlicht in: | IEEE transactions on signal processing 2018-05, Vol.66 (10), p.2645-2658 |
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| container_title | IEEE transactions on signal processing |
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| creator | Yellepeddi, Atulya Preisig, James C. |
| description | This paper introduces the graph-structured recursive least squares (GS-RLS) algorithm, which is a very efficient means to track a linear time-varying system when the inputs to the system have structure that can be modeled using a decomposable Gaussian graphical model. For graphs with small clique sizes, it is shown that GS-RLS can achieve tracking performance very close to that of the conventional RLS algorithm for a fraction of the computational cost. In particular, after proving that the outputs of wide-sense stationary time-varying communication channels have graphical model structure if the inputs are cyclostationary, significant computational gains are realized for adaptive equalization of the time-varying underwater acoustic communication channel using the GS-RLS algorithm. This is verified using field data from the SPACE08 underwater acoustic communication experiment. |
| doi_str_mv | 10.1109/TSP.2018.2811745 |
| format | Article |
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This is verified using field data from the SPACE08 underwater acoustic communication experiment.</description><subject>adaptive algorithms</subject><subject>Adaptive equalizers</subject><subject>Graphical models</subject><subject>Hidden Markov models</subject><subject>Particle separators</subject><subject>Random variables</subject><subject>Signal processing algorithms</subject><subject>Time-varying systems</subject><subject>underwater communication</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhoMoOKf3gjf5A535aNrkcsw5BwOFTfSupEnqol0bk3Qwf4E_2-4Dr87hnPM-HB4AbjEaYYzE_Wr5MiII8xHhGOcpOwMDLFKcoDTPzvseMZownr9fgqsQPhHCaSqyAfidVpVV1jQRLnchmg1ceam-bPMB32xcwwej2o1rgyxrA2deunWyjL5TsfNGw3njuhigbDQcO1dbJaNtGxhbONbSRbs1cPrdydr-HBcH5GSn6jbEw0T63QlyDS4qWQdzc6pD8Po4XU2eksXzbD4ZLxJFMhoTJhQhAmGCOaOZSIlmFVJEUU44Vawk2OSSZxXKuSaaEJVnKWLMkFIoWWpNhwAducq3IXhTFc7bTf9HgVGxN1n0Jou9yeJkso_cHSPWGPN_zikSNKf0D4jmcmE</recordid><startdate>20180515</startdate><enddate>20180515</enddate><creator>Yellepeddi, Atulya</creator><creator>Preisig, James C.</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-2703-4748</orcidid></search><sort><creationdate>20180515</creationdate><title>Efficient System Tracking With Decomposable Graph-Structured Inputs and Application to Adaptive Equalization With Cyclostationary Inputs</title><author>Yellepeddi, Atulya ; Preisig, James C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c263t-59c22901218536942d5f0c2c38283c5b21e7a86f078d2d22c764055e2b9cabdd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>adaptive algorithms</topic><topic>Adaptive equalizers</topic><topic>Graphical models</topic><topic>Hidden Markov models</topic><topic>Particle separators</topic><topic>Random variables</topic><topic>Signal processing algorithms</topic><topic>Time-varying systems</topic><topic>underwater communication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yellepeddi, Atulya</creatorcontrib><creatorcontrib>Preisig, James C.</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><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yellepeddi, Atulya</au><au>Preisig, James C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficient System Tracking With Decomposable Graph-Structured Inputs and Application to Adaptive Equalization With Cyclostationary Inputs</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2018-05-15</date><risdate>2018</risdate><volume>66</volume><issue>10</issue><spage>2645</spage><epage>2658</epage><pages>2645-2658</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>This paper introduces the graph-structured recursive least squares (GS-RLS) algorithm, which is a very efficient means to track a linear time-varying system when the inputs to the system have structure that can be modeled using a decomposable Gaussian graphical model. 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| subjects | adaptive algorithms Adaptive equalizers Graphical models Hidden Markov models Particle separators Random variables Signal processing algorithms Time-varying systems underwater communication |
| title | Efficient System Tracking With Decomposable Graph-Structured Inputs and Application to Adaptive Equalization With Cyclostationary Inputs |
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