bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0476595 |
utime |
20240111140943.5 |
mtime |
20170731235959.9 |
SCOPUS |
85029307166 |
DOI |
10.5220/0006417104490458 |
title
(primary) (eng) |
Initialization of Recursive Mixture-based Clustering with Uniform Components |
specification |
page_count |
10 s. |
media_type |
C |
|
serial |
ARLID |
cav_un_epca*0476594 |
ISBN |
978-989-758-263-9 |
title
|
Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017) |
part_title |
Volume 1 |
page_num |
449-458 |
publisher |
place |
Setúbal |
name |
SCITEPRESS |
year |
2017 |
|
|
keyword |
Mixture-based Clustering |
keyword |
Recursive Mixture Estimation |
keyword |
Uniform Components |
author
(primary) |
ARLID |
cav_un_auth*0108105 |
name1 |
Suzdaleva |
name2 |
Evgenia |
full_dept (cz) |
Zpracování signálů |
full_dept (eng) |
Department of Signal Processing |
department (cz) |
ZS |
department (eng) |
ZS |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
country |
RU |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101167 |
name1 |
Nagy |
name2 |
Ivan |
full_dept (cz) |
Zpracování signálů |
full_dept |
Department of Signal Processing |
department (cz) |
ZS |
department |
ZS |
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*0205791 |
name1 |
Pecherková |
name2 |
Pavla |
full_dept (cz) |
Zpracování signálů |
full_dept |
Department of Signal Processing |
department (cz) |
ZS |
department |
ZS |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
country |
CZ |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0330517 |
name1 |
Likhonina |
name2 |
Raissa |
full_dept (cz) |
Zpracování signálů |
full_dept |
Department of Signal Processing |
department (cz) |
ZS |
department |
ZS |
institution |
UTIA-B |
full_dept |
Department of Signal Processing |
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 |
|
abstract
(eng) |
The paper deals with a task of initialization of the recursive mixture estimation for the case of uniform components. This task is significant as a part of mixture-based clustering, where data clusters are described by the uniform distributions. The issue is extensively explored for normal components. However, sometimes the assumption of normality is not suitable or limits potential application areas (e.g., in the case of data with fixed bounds). The use of uniform components can be beneficial for these cases. Initialization is always a critical task of the mixture estimation. Within the considered recursive estimation algorithm the key point of its initialization is a choice of initial statistics of components. The paper explores several initialization approaches and compares results of clustering with a theoretical counterpart. Experiments with real data are demonstrated. |
action |
ARLID |
cav_un_auth*0348184 |
name |
The 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017) |
dates |
20170726 |
mrcbC20-s |
20170728 |
place |
Madrid |
country |
ES |
|
RIV |
BB |
FORD0 |
10000 |
FORD1 |
10100 |
FORD2 |
10103 |
reportyear |
2018 |
num_of_auth |
4 |
mrcbC52 |
4 A hod 4ah 20231122142550.2 |
presentation_type |
PR |
inst_support |
RVO:67985556 |
permalink |
http://hdl.handle.net/11104/0273534 |
mrcbC64 |
1 Department of Signal Processing UTIA-B 10103 STATISTICS & PROBABILITY |
confidential |
S |
arlyear |
2017 |
mrcbTft |
\nSoubory v repozitáři: suzdaleva-0476595.pdf |
mrcbU14 |
85029307166 SCOPUS |
mrcbU24 |
PUBMED |
mrcbU34 |
WOS |
mrcbU56 |
pdf |
mrcbU63 |
cav_un_epca*0476594 Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017) Volume 1 978-989-758-263-9 449 458 Setúbal SCITEPRESS 2017 |
|