| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0328917 |
| utime |
20240103192028.6 |
| mtime |
20090915235959.9 |
| title
(primary) (eng) |
Log-Normal Merging for Distributed System Identification |
| specification |
| page_count |
6 s. |
| media_type |
www |
|
| serial |
| ARLID |
cav_un_epca*0328916 |
| title
|
Proceedings of the 15th IFAC Symposium on System Identification |
| page_num |
1-6 |
| publisher |
| place |
Saint Malo |
| name |
IFAC |
| year |
2009 |
|
|
| title
(cze) |
Lognormální skládání pravděpodobností pro distribuovanou identifikaci systémů |
| keyword |
Bayesian Methods |
| keyword |
Hybrid and Distributed System Identification |
| keyword |
Particle Filtering/Monte Carlo Methods |
| author
(primary) |
| 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. |
|
| 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. |
|
| source |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
GP102/08/P250 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0241640 |
|
| project |
| project_id |
GA102/08/0567 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239566 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Growing interest in applications of distributed systems, such as multi-agent systems, increases demands on identification of distributed systems from partial information sources collected by local agents. We are concerned with fully distributed scenario where system is identified by multiple agents, which do not estimate state of the whole system but only its local `state'. The resulting estimate is obtained by merging of marginal and conditional posterior probability density functions (pdf) on such local states. We investigate the use of recently proposed non-parametric log-normal merging of such `fragmental' pdfs for this task. We derive a projection of the optimal merger to the class of weighted empirical pdfs and mixtures of Gaussian pdfs. We illustrate the use of this technique on distributed identification of a controlled autoregressive model. |
| abstract
(cze) |
S rozvojem distribuovaných sstémů se zvyšují nároky na jejich identifikaci z distribuovaných a neúplných měření. Tento článek se zabývá plně distribuovaným scénářem, kde každý lokální agent identifikuje pouze svoji část systému. Identifikace celého systému je získána složením aposteriorních distribucí jednotlivých agentů. K tomu je použita nová technika log-normálního skládání hustot pravdepodobnosti. Postup je ilustrován na jednoduchém příkladu. |
| action |
| ARLID |
cav_un_auth*0253846 |
| name |
15th IFAC Symposium on System Identification |
| place |
Saint Malo |
| dates |
06.07.2009-08.07.2009 |
| country |
FR |
|
| reportyear |
2010 |
| RIV |
BC |
| permalink |
http://hdl.handle.net/11104/0175102 |
| arlyear |
2009 |
| mrcbU63 |
cav_un_epca*0328916 Proceedings of the 15th IFAC Symposium on System Identification 1 6 Saint Malo IFAC 2009 |
|