| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0041786 |
| utime |
20240103182809.9 |
| mtime |
20061005235959.9 |
| title
(primary) (eng) |
Towards Bayesian filtering on restricted support |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0076872 |
| ISBN |
978-1-4244-0579-4 |
| title
|
Proceedings of the NSSPW'06 Workshop |
| page_num |
1-4 |
| publisher |
| place |
Cambridge |
| name |
University of Cambridge |
| year |
2006 |
|
|
| title
(cze) |
Bayesovská filtrace na omezeném suportu |
| keyword |
bayesian estimation |
| keyword |
state model |
| keyword |
restricted support |
| author
(primary) |
| ARLID |
cav_un_auth*0101175 |
| name1 |
Pavelková |
| name2 |
Lenka |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101124 |
| name1 |
Kárný |
| name2 |
Miroslav |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101207 |
| name1 |
Šmídl |
| name2 |
Václav |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| COSATI |
09I |
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
1ET100750401 |
| agency |
GA AV ČR |
| ARLID |
cav_un_auth*0001792 |
|
| project |
| project_id |
2C06001 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0217685 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Linear state-space model with uniformly distributed innovations is considered. Its state and parameters are estimated under hard physical bounds. Off-line maximum a posteriori probability estimation reduces to linear programming. No approximation is required for sole estimation of either model parameters or states. The noise bounds are estimated in both cases. The algorithm is extended to: (i) on-line mode by estimating within a sliding window, and (ii) joint state and parameter estimation. This approach may be used as a starting point for full Bayesian treatment of distributions with restricted support. |
| abstract
(cze) |
Je uvažován lineární stavový model s rovnoměrně rozloženými inovacemi. Stavy a parametry modelu jsou odhadování při uvažování přísných fyzikálních omezení. Maximálně věrohodný off-line odhad je redukován na lineární programování. Pro samostatný odhad buď parametrů anebo stavu není třeba aproximace. Meze šumu jsou odhadovány v obou případech. Algoritmus je dále rozšířen na: (i) on-line režim pomocí odhadu v klouzavém okně a (ii) společný odhad stavu a parametrů. Tento přístup může být použit jako výchozí bod pro Bayesovský přístup k distribucím s omezeným suportem. |
| action |
| ARLID |
cav_un_auth*0217684 |
| name |
Nonlinear Statistical Siganl Processing Workshop 2006 |
| place |
Cambridge |
| dates |
13.09.2006-15.09.2006 |
| country |
GB |
|
| reportyear |
2010 |
| RIV |
BC |
| permalink |
http://hdl.handle.net/11104/0135159 |
| arlyear |
2006 |
| mrcbU63 |
cav_un_epca*0076872 Proceedings of the NSSPW'06 Workshop 978-1-4244-0579-4 1 4 Cambridge University of Cambridge 2006 |
|