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<bibitem type="C">   <ARLID>0312650</ARLID> <utime>20240111140706.7</utime><mtime>20081008235959.9</mtime>         <title language="eng" primary="1">Problem of State Filtering  in Case of Partially Known System Matrices</title>  <specification> <page_count>6 s.</page_count> <media_type>CD</media_type> </specification>   <serial><ARLID>cav_un_epca*0312649</ARLID><ISBN>978-961-264-003-3</ISBN><title>Proceedings of the 9th International PhD Workshop on Systems and Control</title><part_num/><part_title/><page_num>1-6</page_num><publisher><place>Ljubljana</place><name>Jožef Stefan Institute</name><year>2008</year></publisher><editor><name1>Gašperin</name1><name2>Matej</name2></editor><editor><name1>Pregelj</name1><name2>Boštjan</name2></editor></serial>   <title language="cze" primary="0">Úloha filtrace stavu v případě částečně známých matic modelu</title>    <keyword>state model</keyword>   <keyword>uniform innovations</keyword>   <keyword>state filtration</keyword>   <keyword>parameter estimation</keyword>    <author primary="1"> <ARLID>cav_un_auth*0101175</ARLID> <name1>Pavelková</name1> <name2>Lenka</name2> <institution>UTIA-B</institution> <full_dept>Department of Adaptive Systems</full_dept>  <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>   <source> <source_type>soubor pdf</source_type> <url>http://library.utia.cas.cz/separaty/2008/AS/pavelkova-problem%20of%20state%20filtering%20%20in%20case%20of%20partially%20known%20system%20matrices.pdf</url> <source_size>120kB</source_size> </source>        <cas_special> <project> <project_id>1M0572</project_id> <agency>GA MŠk</agency> <ARLID>cav_un_auth*0001814</ARLID> </project> <project> <project_id>2C06001</project_id> <agency>GA MŠk</agency> <ARLID>cav_un_auth*0217685</ARLID> </project> <research> <research_id>CEZ:AV0Z10750506</research_id> </research>  <abstract language="eng" primary="1">The linear state-space model with uniform innovations (LU model)  proposed in previous author's work is extended here. The states  and parameters of LU model are estimated under hard physical  bounds. The estimation of the innovation boundaries is also  included. Maximum a posteriori probability estimation reduces to  the linear programming. The on-line estimation is running within  the sliding window.    Compared to the original model, we consider that model matrices  can be time-variant. Also, offset terms are included. We present  the problem of the joint parameter and state estimation, i.e., the  state filtering with unknown model matrices. The ambiguity in the  state estimates can be substantially decreased by the partial  knowledge of some entries in the model matrices. The simple  example illustrates this approach.</abstract> <abstract language="cze" primary="0">Příspěvek rozšiřuje rovnoměrný stavový model, zavedený v předchozích příspěvcích autora. Stavy a parametry jsou odhadované za přítomnosti pevných omezení, odhad mezí šumu je rovněž zahrnut. Maximálně věrohodný odhad je získán pomocí lineárního  programování. On-line odhad probíhá na posuvném okně. Matice modelu mohou být časově proměnné. Příspěvek se zabývá sdruženým odhadem stavu a parametrů. Ukazuje, že částečná znalost matic modelu může snížit nebo i odstranit   víceznačnost odhadu.</abstract>  <action target="EUR"> <ARLID>cav_un_auth*0242520</ARLID> <name>International PhD Workshop on Systems and Control</name> <place>Izola</place> <dates>01.10.2008-03.10.2008</dates>  <country>SI</country> </action>    <reportyear>2009</reportyear>  <RIV>BC</RIV>      <permalink>http://hdl.handle.net/11104/0163655</permalink>        <arlyear>2008</arlyear>       <unknown tag="mrcbU56"> soubor pdf 120kB </unknown> <unknown tag="mrcbU63"> cav_un_epca*0312649 Proceedings of the 9th International PhD Workshop on Systems and Control 978-961-264-003-3 1 6 Ljubljana Jožef Stefan Institute 2008 </unknown> <unknown tag="mrcbU67"> Gašperin Matej 340 </unknown> <unknown tag="mrcbU67"> Pregelj Boštjan 340 </unknown> </cas_special> </bibitem>