bibtype J - Journal Article
ARLID 0431479
utime 20240103204610.0
mtime 20140912235959.9
WOS 000342159700009
SCOPUS 84907191888
DOI 10.1109/LSP.2014.2353652
title (primary) (eng) Sequential Estimation of Mixtures in Diffusion Networks
specification
page_count 5 s.
media_type E
serial
ARLID cav_un_epca*0253212
ISSN 1070-9908
title IEEE Signal Processing Letters
volume_id 22
volume 2 (2015)
page_num 197-201
publisher
name Institute of Electrical and Electronics Engineers
keyword distributed estimation
keyword mixture models
keyword bayesian inference
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*0306030
name1 Reichl
name2 Jan
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0306051
name1 Djurić
name2 P. M.
country US
source
url http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431479.pdf
cas_special
project
project_id GP14-06678P
agency GA ČR
country CZ
ARLID cav_un_auth*0303543
abstract (eng) The letter studies the problem of sequential estimation of mixtures in diffusion networks whose nodes communicate only with their adjacent neighbors. The adopted quasi-Bayesian approach yields a probabilistically consistent and computationally non-intensive and fast method, applicable to a wide class of mixture models with unknown component parameters and weights. Moreover, if conjugate priors are used for inferring the component parameters, the solution attains a closed analytic form.
reportyear 2017
RIV BB
num_of_auth 3
mrcbC52 4 A 4a 20231122140419.8
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0236075
confidential S
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mrcbT16-4 Q1
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arlyear 2015
mrcbTft \nSoubory v repozitáři: dedecius-0431479.pdf
mrcbU14 84907191888 SCOPUS
mrcbU34 000342159700009 WOS
mrcbU63 cav_un_epca*0253212 IEEE Signal Processing Letters 1070-9908 1558-2361 Roč. 22 č. 2 2015 197 201 Institute of Electrical and Electronics Engineers