| bibtype |
J -
Journal Article
|
| ARLID |
0370448 |
| utime |
20240103200153.9 |
| mtime |
20120109235959.9 |
| WOS |
000298786900001 |
| SCOPUS |
84855462282 |
| DOI |
10.1002/acs.1270 |
| title
(primary) (eng) |
Parameter tracking with partial forgetting method |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0256772 |
| ISSN |
0890-6327 |
| title
|
International Journal of Adaptive Control and Signal Processing |
| volume_id |
26 |
| volume |
1 (2012) |
| page_num |
1-12 |
| publisher |
|
|
| keyword |
regression models |
| keyword |
model |
| keyword |
parameter estimation |
| keyword |
parameter tracking |
| author
(primary) |
| ARLID |
cav_un_auth*0242543 |
| name1 |
Dedecius |
| name2 |
Kamil |
| 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*0101167 |
| name1 |
Nagy |
| name2 |
Ivan |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| 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 |
| 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 |
GA102/08/0567 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239566 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
This paper concerns the Bayesian tracking of slowly varying parameters of a linear stochastic regression model. The modelled and predicted system output is assumed to possess time-varying mean value, whereas its dynamics are relatively stable. The proposed estimation method models the system output mean value by time-varying offset. It formulates three extreme hypotheses on model parameters’ variability: (i) no parameter varies; (ii) all parameters vary; and (iii) the offset varies. The Bayesian paradigm then provides a mixture as posterior distribution, which is appropriately projected to a feasible class. Exponential forgetting at ‘second’ hypotheses level allows tracking of slow variations of respective hypotheses. |
| reportyear |
2012 |
| RIV |
BB |
| num_of_auth |
3 |
| mrcbC52 |
4 A 4a 20231122134847.8 |
| permalink |
http://hdl.handle.net/11104/0204249 |
| mrcbT16-e |
AUTOMATIONCONTROLSYSTEMS|ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-f |
1.334 |
| mrcbT16-g |
0.323 |
| mrcbT16-h |
6 |
| mrcbT16-i |
0.00262 |
| mrcbT16-j |
0.522 |
| mrcbT16-k |
809 |
| mrcbT16-l |
65 |
| mrcbT16-s |
0.779 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
48.308 |
| mrcbT16-C |
52.469 |
| mrcbT16-D |
Q3 |
| mrcbT16-E |
Q2 |
| arlyear |
2012 |
| mrcbTft |
\nSoubory v repozitáři: dedecius-0370448.pdf |
| mrcbU14 |
84855462282 SCOPUS |
| mrcbU34 |
000298786900001 WOS |
| mrcbU63 |
cav_un_epca*0256772 International Journal of Adaptive Control and Signal Processing 0890-6327 1099-1115 Roč. 26 č. 1 2012 1 12 Wiley |
|