| bibtype |
J -
Journal Article
|
| ARLID |
0500102 |
| utime |
20240111141013.8 |
| mtime |
20190118235959.9 |
| SCOPUS |
85058892691 |
| WOS |
000455720600015 |
| DOI |
10.1109/TSP.2018.2887185 |
| title
(primary) (eng) |
Gradient Algorithms for Complex Non-Gaussian Independent Component/Vector Extraction, Question of Convergence |
| specification |
| page_count |
15 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0256727 |
| ISSN |
1053-587X |
| title
|
IEEE Transactions on Signal Processing |
| volume_id |
67 |
| volume |
4 (2019) |
| page_num |
1050-1064 |
|
| keyword |
Blind source separation |
| keyword |
blind source extraction |
| keyword |
independent component analysis |
| keyword |
independent vector analysis |
| author
(primary) |
| ARLID |
cav_un_auth*0230113 |
| name1 |
Koldovský |
| name2 |
Z. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GA17-00902S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0345929 |
|
| abstract
(eng) |
We revise the problem of extracting one independent component from an instantaneous linear mixture of signals. The mixing matrix is parameterized by two vectors: one column of the mixing matrix, and one row of the demixing matrix. The separation is based on the non-Gaussianity of the source of interest, while the remaining background signals are assumed to be Gaussian. Three gradient-based estimation algorithms are derived using the maximum likelihood principle and are compared with the Natural Gradient algorithm for Independent Component Analysis and with One-Unit FastICA based on negentropy maximization. The ideas and algorithms are also generalized to the extraction of a vector component when the extraction proceeds jointly from a set of instantaneous mixtures. Throughout this paper, we address the problem concerning the size of the region of convergence for which the algorithms guarantee the extraction of the desired source. We show that the size is influenced by the signal-to-interference ratio on the input channels. Simulations comparing several algorithms confirm this observation. They show a different size of the region of convergence under a scenario in which the source of interest is dominant or weak. Here, our proposed modificationsof the gradient methods, taking into account the dominance/weakness of the source, showimproved global convergence.\n |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2020 |
| num_of_auth |
2 |
| mrcbC52 |
4 A hod 4ah 20231122143746.0 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0293321 |
| mrcbC64 |
1 Department of Stochastic Informatics UTIA-B 20201 ENGINEERING, ELECTRICAL & ELECTRONIC |
| confidential |
S |
| mrcbC86 |
1* Article|Proceedings Paper Engineering Electrical Electronic |
| mrcbC91 |
C |
| mrcbT16-e |
ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-j |
1.718 |
| mrcbT16-s |
2.098 |
| mrcbT16-B |
91.914 |
| mrcbT16-D |
Q1* |
| mrcbT16-E |
Q1 |
| arlyear |
2019 |
| mrcbTft |
\nSoubory v repozitáři: tichavsky-0500102.pdf |
| mrcbU14 |
85058892691 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000455720600015 WOS |
| mrcbU56 |
1727 kB |
| mrcbU63 |
cav_un_epca*0256727 IEEE Transactions on Signal Processing 1053-587X 1941-0476 Roč. 67 č. 4 2019 1050 1064 |
|