| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0394050 |
| utime |
20240103202719.3 |
| mtime |
20131001235959.9 |
| title
(primary) (eng) |
Adaptive Importance Sampling in Particle Filtering |
| specification |
| page_count |
8 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0394049 |
| ISBN |
978-605-86311-1-3 |
| title
|
Proceeding of the 16th International Conference on Information Fusion |
| publisher |
| place |
Istanbul |
| name |
ISIF |
| year |
2013 |
|
|
| keyword |
importance sampling |
| keyword |
sequential monte carlo |
| keyword |
sufficient statistics |
| author
(primary) |
| ARLID |
cav_un_auth*0101207 |
| name1 |
Šmídl |
| name2 |
Václav |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| 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*0228606 |
| name1 |
Hofman |
| name2 |
Radek |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| 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 |
VG20102013018 |
| agency |
GA MV |
| ARLID |
cav_un_auth*0265869 |
|
| project |
| project_id |
GAP102/11/0437 |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0273082 |
|
| abstract
(eng) |
Computational efficiency of the particle filter, as a method based on importance sampling, depends on the choice of the proposal density. Various default schemes, such as the bootstrap proposal, can be very inefficient in demanding applications. Adaptive particle filtering is a general class of algorithms that adapt the proposal function using the observed data. Adaptive importance sampling is a technique based on parametrization of the proposal and recursive estimation of the parameters. In this paper, we investigate the use of the adaptive importance sampling in the context of particle filtering. Specifically, we propose and test several options of parameter initialization and particle association. The technique is applied in a demanding scenario of tracking an atmospheric release of radiation. In this scenario, the likelihood of the observations is rather sharp and its evaluation is computationally expensive. Hence, the overhead of the adaptation procedure is negligible and the proposed adaptive technique clearly improves over non-adaptive methods. |
| action |
| ARLID |
cav_un_auth*0292301 |
| name |
16th International Conference on Information Fusion |
| place |
Istanbul |
| dates |
09.07.2013-12.07.2013 |
| country |
TR |
|
| reportyear |
2014 |
| RIV |
BC |
| presentation_type |
PR |
| permalink |
http://hdl.handle.net/11104/0224340 |
| mrcbC61 |
1 |
| arlyear |
2013 |
| mrcbU63 |
cav_un_epca*0394049 Proceeding of the 16th International Conference on Information Fusion 978-605-86311-1-3 Istanbul ISIF 2013 |
|