bibtype J - Journal Article
ARLID 0532740
utime 20240103224500.3
mtime 20201005235959.9
WOS 000576252300002
DOI 10.1109/TSP.2020.3022827
title (primary) (eng) Cramér-Rao Bounds for Complex-Valued Independent Component Extraction: Determined and Piecewise Determined Mixing Models
specification
page_count 14 s.
media_type P
serial
ARLID cav_un_epca*0256727
ISSN 1053-587X
title IEEE Transactions on Signal Processing
volume_id 68
volume 10 (2020)
page_num 5230-5243
keyword Blind source extraction
keyword Cramér-Rao lower bound
keyword Dynamic Mixing Models
keyword Independent Componenet Analysis
author (primary)
ARLID cav_un_auth*0350114
name1 Kautský
name2 V.
country CZ
author
ARLID cav_un_auth*0230113
name1 Koldovský
name2 Z.
country CZ
author
ARLID cav_un_auth*0101212
name1 Tichavský
name2 Petr
institution UTIA-B
full_dept (cz) Stochastická informatika
full_dept Department of Stochastic Informatics
department (cz) SI
department SI
full_dept Department of Stochastic Informatics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0396616
name1 Zarzoso
name2 V.
country FR
source
url http://library.utia.cas.cz/separaty/2020/SI/tichavsky-0532740.pdf
source
url https://ieeexplore.ieee.org/document/9195105
cas_special
project
project_id GA20-17720S
agency GA ČR
country CZ
ARLID cav_un_auth*0396617
abstract (eng) Blind source extraction (BSE) aims at recovering an unknown source signal of interest from the observation of instantaneous linear mixtures of the sources. This paper presents Cramér-Rao lower bounds (CRLB) for the complex-valued BSE problem based on the assumption that the target signal is independent of the other signals. The target source is assumed to be non-Gaussian or non-circular Gaussian while the other signals (background) are circular Gaussian or non-Gaussian. The results confirm some previous observations known for the real domain and yield new results for the complex domain. Also, the CRLB for independent component extraction (ICE) is shown to coincide with that for independent component analysis (ICA) when the non-Gaussianity of background is taken into account. Second, we extend the CRLB analysis to piecewise determined mixing models, where the observed signals are assumed to obey the determined mixing model within short blocks where the mixing matrices can be varying from block to block. This model has applications, for instance, when separating dynamic mixtures. Either the mixing vector or the separating vector corresponding to the target source is assumed to be constant across the blocks. The CRLBs for the parameters of these models bring new performance limits for the BSEproblem.\n
result_subspec WOS
RIV BB
FORD0 20000
FORD1 20200
FORD2 20201
reportyear 2021
num_of_auth 4
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0311169
confidential S
mrcbC86 2 Article Engineering Electrical Electronic
mrcbC91 C
mrcbT16-e ENGINEERINGELECTRICALELECTRONIC
mrcbT16-i 8.68988
mrcbT16-j 1.701
mrcbT16-s 1.638
mrcbT16-B 91.464
mrcbT16-D Q1*
mrcbT16-E Q1
arlyear 2020
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 000576252300002 WOS
mrcbU63 cav_un_epca*0256727 IEEE Transactions on Signal Processing 1053-587X 1941-0476 Roč. 68 č. 10 2020 5230 5243