bibtype C - Conference Paper (international conference)
ARLID 0483430
utime 20240111140953.6
mtime 20171218235959.9
SCOPUS 85051123821
WOS 000428438100026
DOI 10.1109/CAMSAP.2017.8313082
title (primary) (eng) Under-Determined Tensor Diagonalization for Decomposition of Difficult Tensors
specification
page_count 4 s.
media_type C
serial
ARLID cav_un_epca*0483428
ISBN 978-1-5386-1250-7
title IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017
page_num 263-266
publisher
place Piscataway
name IEEE
year 2017
keyword canonical polyadic decomposition
keyword tensor decomposition
keyword matrix multiplication
author (primary)
ARLID cav_un_auth*0101212
share 70
name1 Tichavský
name2 Petr
institution UTIA-B
full_dept (cz) Stochastická informatika
full_dept (eng) Department of Stochastic Informatics
department (cz) SI
department (eng) SI
full_dept Department of Stochastic Informatics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0274170
share 20
name1 Phan
name2 A. H.
country JP
author
ARLID cav_un_auth*0274171
share 10
name1 Cichocki
name2 A.
country JP
source
source_type pdf
url http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0483430.pdf
source_size 117623
cas_special
project
ARLID cav_un_auth*0345929
project_id GA17-00902S
agency GA ČR
abstract (eng) This paper deals with the Cramer-Rao Lower Bound (CRLB) for a novel blind source separation method called Independent Component Extraction (ICE). Compared to Independent Component Analysis (ICA), ICE aims to extract only one independent signal from a linear mixture. The target signal is assumed to be non-Gaussian, while the other signals, which are not separated, are modeled as a Gaussian mixture. A CRLBinduced Bound (CRIB) for Interference-to-Signal Ratio (ISR)\nis derived. Numerical simulations compare the CRIB with the performance of an ICA and an ICE algorithm. The results show good agreement between the theory and the empirical results.
action
ARLID cav_un_auth*0355384
name CAMSAP 2017 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
dates 20171210
mrcbC20-s 20171213
place Curacao
country NL
RIV BB
FORD0 10000
FORD1 10100
FORD2 10103
reportyear 2018
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0278758
confidential S
mrcbC83 RIV/67985556:_____/17:00483430!RIV18-AV0-67985556 191975733 Doplnění UT WOS a Scopus
mrcbC83 RIV/67985556:_____/17:00483430!RIV18-GA0-67985556 191965061 Doplnění UT WOS a Scopus
mrcbC86 n.a. Proceedings Paper Engineering Electrical Electronic|Mathematics Applied
mrcbC86 3+4 Proceedings Paper Engineering Electrical Electronic|Mathematics Applied
mrcbC86 3+4 Proceedings Paper Engineering Electrical Electronic|Mathematics Applied
arlyear 2017
mrcbU14 85051123821 SCOPUS
mrcbU24 PUBMED
mrcbU34 000428438100026 WOS
mrcbU56 pdf 117623
mrcbU63 cav_un_epca*0483428 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017 978-1-5386-1250-7 263 266 Piscataway IEEE 2017