| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0461565 |
| utime |
20240111140922.6 |
| mtime |
20160808235959.9 |
| SCOPUS |
85013029030 |
| WOS |
000392610900063 |
| DOI |
10.5220/0005982805270534 |
| title
(primary) (eng) |
Comparison of Various Definitions of Proximity in Mixture Estimation |
| specification |
| page_count |
8 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0461767 |
| ISBN |
978-989-758-198-4 |
| title
|
Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) |
| part_title |
Volume 1 |
| page_num |
527-534 |
| publisher |
| place |
Setubal |
| name |
SCITEPRESS |
| year |
2016 |
|
|
| keyword |
classification |
| keyword |
recursive mixture estimation |
| keyword |
proximity |
| keyword |
Bayesian methods |
| keyword |
mixture based clustering |
| author
(primary) |
| ARLID |
cav_un_auth*0101167 |
| full_dept (cz) |
Zpracování signálů |
| full_dept (eng) |
Department of Signal Processing |
| department (cz) |
ZS |
| department (eng) |
ZS |
| full_dept |
Department of Signal Processing |
| name1 |
Nagy |
| name2 |
Ivan |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0108105 |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| full_dept |
Department of Signal Processing |
| name1 |
Suzdaleva |
| name2 |
Evgenia |
| institution |
UTIA-B |
| country |
RU |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0205791 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Signal Processing |
| name1 |
Pecherková |
| name2 |
Pavla |
| institution |
UTIA-B |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0321440 |
| project_id |
GA15-03564S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
Classification is one of the frequently demanded tasks in data analysis. There exists a series of approaches in this area. This paper is oriented towards classification using the mixture model estimation, which is based on detection of density clusters in the data space and fitting the component models to them. A chosen function of proximity of the actually measured data to individual mixture components and the component shape play a significant role in solving the mixture-based classification task. This paper considers definitions of the proximity for several types of distributions describing the mixture components and compares their properties with respect to speed and quality of the resulting estimation interpreted as a classification task. Normal, exponential and uniform distributions as the most important models used for describing both Gaussian and non-Gaussian data are considered. Illustrative experiments with results of the comparison are provided. |
| action |
| ARLID |
cav_un_auth*0332301 |
| name |
International Conference on Informatics in Control, Automation and Robotics /13./ (ICINCO 2016) |
| dates |
20160729 |
| mrcbC20-s |
20160731 |
| place |
Lisbon |
| country |
PT |
|
| RIV |
BB |
| reportyear |
2017 |
| num_of_auth |
3 |
| mrcbC52 |
4 A hod 4ah 20231122141811.8 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0261344 |
| mrcbC64 |
1 Department of Signal Processing UTIA-B 10103 STATISTICS & PROBABILITY |
| confidential |
S |
| mrcbC86 |
n.a. Proceedings Paper Automation Control Systems|Engineering Electrical Electronic|Robotics |
| arlyear |
2016 |
| mrcbTft |
\nSoubory v repozitáři: suzdaleva-0461565.pdf |
| mrcbU14 |
85013029030 SCOPUS |
| mrcbU34 |
000392610900063 WOS |
| mrcbU56 |
pdf |
| mrcbU63 |
cav_un_epca*0461767 Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) Volume 1 978-989-758-198-4 527 534 Setubal SCITEPRESS 2016 |
|