Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise
The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisa...
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 76 |
|---|---|
| container_issue | |
| container_start_page | 71 |
| container_title | |
| container_volume | |
| creator | Larkowski, T. Linden, J.G. Vinsonneau, B. Burnham, K.J. |
| description | The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisation is exploited. Two standard least squares methods are utilised to separately determine, firstly, the system parameter vector and, secondly, the input measurement noise variance together with auto-correlation elements of the output noise. Since it is based on the least squares technique, the computational complexity of the algorithm is relatively low. A Monte-Carlo simulation compares the developed technique with other errors-in-variables identification methods. |
| doi_str_mv | 10.1109/ICSEng.2008.88 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4616616</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4616616</ieee_id><sourcerecordid>4616616</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-e1e3ea5151a2411857cae72e102a9a6b2c51dbf7caf0ff203f53be83a7902b953</originalsourceid><addsrcrecordid>eNotkE9LAzEQxQMiaGuvXrzkC2zNJJv9c5Rl1UKxh6rXMtudaKTd1CQr1k9vig4P5vHj8RiGsWsQcwBR3y6adTu8zaUQ1byqzthElEWtlVIgztnkhGtZ54W8YLMQPkSaPNc5wCX7WfQ0RGvsFqN1A3eGt947HzI7ZK_oLXY7Cnx9DJH2gX9Z5O13pKGnnjduf6AhYEx-SRgiX3-O6FPcOM_jO_EGA50qG7dzo0-x1RgPY-RPzga6YucGd4Fm_3vKXu7b5-YxW64eFs3dMrNQ6pgRkCLUoAFlOrnS5RaplARCYo1FJ7ca-s4kaoQxUiijVUeVwrIWsktfmLKbv15LRJuDt3v0x01eQJGkfgHg6V7p</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Larkowski, T. ; Linden, J.G. ; Vinsonneau, B. ; Burnham, K.J.</creator><creatorcontrib>Larkowski, T. ; Linden, J.G. ; Vinsonneau, B. ; Burnham, K.J.</creatorcontrib><description>The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisation is exploited. Two standard least squares methods are utilised to separately determine, firstly, the system parameter vector and, secondly, the input measurement noise variance together with auto-correlation elements of the output noise. Since it is based on the least squares technique, the computational complexity of the algorithm is relatively low. A Monte-Carlo simulation compares the developed technique with other errors-in-variables identification methods.</description><identifier>ISBN: 0769533310</identifier><identifier>ISBN: 9780769533315</identifier><identifier>DOI: 10.1109/ICSEng.2008.88</identifier><identifier>LCCN: 2008929462</identifier><language>eng</language><publisher>IEEE</publisher><subject>bias compensation ; bilinear parametrisation ; Correlation ; Covariance matrix ; Equations ; errors-in-variables ; identification ; Instruments ; Mathematical model ; Noise ; Noise measurement</subject><ispartof>2008 19th International Conference on Systems Engineering, 2008, p.71-76</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4616616$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4616616$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Larkowski, T.</creatorcontrib><creatorcontrib>Linden, J.G.</creatorcontrib><creatorcontrib>Vinsonneau, B.</creatorcontrib><creatorcontrib>Burnham, K.J.</creatorcontrib><title>Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise</title><title>2008 19th International Conference on Systems Engineering</title><addtitle>ICSENG</addtitle><description>The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisation is exploited. Two standard least squares methods are utilised to separately determine, firstly, the system parameter vector and, secondly, the input measurement noise variance together with auto-correlation elements of the output noise. Since it is based on the least squares technique, the computational complexity of the algorithm is relatively low. A Monte-Carlo simulation compares the developed technique with other errors-in-variables identification methods.</description><subject>bias compensation</subject><subject>bilinear parametrisation</subject><subject>Correlation</subject><subject>Covariance matrix</subject><subject>Equations</subject><subject>errors-in-variables</subject><subject>identification</subject><subject>Instruments</subject><subject>Mathematical model</subject><subject>Noise</subject><subject>Noise measurement</subject><isbn>0769533310</isbn><isbn>9780769533315</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkE9LAzEQxQMiaGuvXrzkC2zNJJv9c5Rl1UKxh6rXMtudaKTd1CQr1k9vig4P5vHj8RiGsWsQcwBR3y6adTu8zaUQ1byqzthElEWtlVIgztnkhGtZ54W8YLMQPkSaPNc5wCX7WfQ0RGvsFqN1A3eGt947HzI7ZK_oLXY7Cnx9DJH2gX9Z5O13pKGnnjduf6AhYEx-SRgiX3-O6FPcOM_jO_EGA50qG7dzo0-x1RgPY-RPzga6YucGd4Fm_3vKXu7b5-YxW64eFs3dMrNQ6pgRkCLUoAFlOrnS5RaplARCYo1FJ7ca-s4kaoQxUiijVUeVwrIWsktfmLKbv15LRJuDt3v0x01eQJGkfgHg6V7p</recordid><startdate>200808</startdate><enddate>200808</enddate><creator>Larkowski, T.</creator><creator>Linden, J.G.</creator><creator>Vinsonneau, B.</creator><creator>Burnham, K.J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200808</creationdate><title>Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise</title><author>Larkowski, T. ; Linden, J.G. ; Vinsonneau, B. ; Burnham, K.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-e1e3ea5151a2411857cae72e102a9a6b2c51dbf7caf0ff203f53be83a7902b953</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>bias compensation</topic><topic>bilinear parametrisation</topic><topic>Correlation</topic><topic>Covariance matrix</topic><topic>Equations</topic><topic>errors-in-variables</topic><topic>identification</topic><topic>Instruments</topic><topic>Mathematical model</topic><topic>Noise</topic><topic>Noise measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Larkowski, T.</creatorcontrib><creatorcontrib>Linden, J.G.</creatorcontrib><creatorcontrib>Vinsonneau, B.</creatorcontrib><creatorcontrib>Burnham, K.J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Larkowski, T.</au><au>Linden, J.G.</au><au>Vinsonneau, B.</au><au>Burnham, K.J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise</atitle><btitle>2008 19th International Conference on Systems Engineering</btitle><stitle>ICSENG</stitle><date>2008-08</date><risdate>2008</risdate><spage>71</spage><epage>76</epage><pages>71-76</pages><isbn>0769533310</isbn><isbn>9780769533315</isbn><abstract>The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisation is exploited. Two standard least squares methods are utilised to separately determine, firstly, the system parameter vector and, secondly, the input measurement noise variance together with auto-correlation elements of the output noise. Since it is based on the least squares technique, the computational complexity of the algorithm is relatively low. A Monte-Carlo simulation compares the developed technique with other errors-in-variables identification methods.</abstract><pub>IEEE</pub><doi>10.1109/ICSEng.2008.88</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISBN: 0769533310 |
| ispartof | 2008 19th International Conference on Systems Engineering, 2008, p.71-76 |
| issn | |
| language | eng |
| recordid | cdi_ieee_primary_4616616 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | bias compensation bilinear parametrisation Correlation Covariance matrix Equations errors-in-variables identification Instruments Mathematical model Noise Noise measurement |
| title | Identification of Errors-in-Variables Systems via Extended Compensated Least Squares for the Case of Coloured Output Noise |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T17%3A28%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Identification%20of%20Errors-in-Variables%20Systems%20via%20Extended%20Compensated%20Least%20Squares%20for%20the%20Case%20of%20Coloured%20Output%20Noise&rft.btitle=2008%2019th%20International%20Conference%20on%20Systems%20Engineering&rft.au=Larkowski,%20T.&rft.date=2008-08&rft.spage=71&rft.epage=76&rft.pages=71-76&rft.isbn=0769533310&rft.isbn_list=9780769533315&rft_id=info:doi/10.1109/ICSEng.2008.88&rft_dat=%3Cieee_6IE%3E4616616%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4616616&rfr_iscdi=true |