bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0328717 |
utime |
20240111140724.7 |
mtime |
20090915235959.9 |
title
(primary) (eng) |
Parameter Estimation With Partial Forgetting Method |
specification |
page_count |
6 s. |
media_type |
www |
|
serial |
ARLID |
cav_un_epca*0329275 |
title
|
Proceedings of the 15th IFAC Symposium on Identification and System Parameter Estimation - SYSID 2009 |
page_num |
534-539 |
publisher |
place |
Saint-Malo |
name |
IFAC |
year |
2009 |
|
|
title
(cze) |
Odhad parametrů metodou parcialního zapomínání |
keyword |
autoregressive models |
keyword |
model |
keyword |
parameter estimation |
keyword |
prediction |
keyword |
regression |
author
(primary) |
ARLID |
cav_un_auth*0242543 |
name1 |
Dedecius |
name2 |
Kamil |
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*0101167 |
name1 |
Nagy |
name2 |
Ivan |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
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*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. |
|
source |
|
cas_special |
project |
project_id |
2C06001 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0217685 |
|
project |
project_id |
GA102/08/0567 |
agency |
GA ČR |
ARLID |
cav_un_auth*0239566 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
The paper proposes a new estimating algorithm for linear parameter varying systems with slowly time-varying parameters when the rate of change of individual parameters is different. It introduces a true probability density function, describing ideally the behaviour of parameters. However, as it is unknown, we search for its best approximation. A convex combination of point estimates, defined by individual hypotheses about the true probability density function, is then approximated by a single density. That serves as the best available description of parameters' behaviour and it is therefore suitable e.g. for prediction purposes. |
abstract
(cze) |
Článek představuje nový rozhodovací algoritmus pro lineární parametry různých systémů s pomalými časově-variačními parametry, kde je velmi malá pravděpodobnost, že se jednotlivé parametry změní. |
action |
ARLID |
cav_un_auth*0253725 |
name |
15th IFAC Symposium on Identification and System Parameter Estimation - SYSID 2009 |
place |
Saint-Malo |
dates |
06.07.2009-08.07.2009 |
country |
FR |
|
reportyear |
2010 |
RIV |
BD |
permalink |
http://hdl.handle.net/11104/0174962 |
arlyear |
2009 |
mrcbU56 |
pdf |
mrcbU63 |
cav_un_epca*0329275 Proceedings of the 15th IFAC Symposium on Identification and System Parameter Estimation - SYSID 2009 534 539 Saint-Malo IFAC 2009 |
|