| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0041069 |
| utime |
20240111140639.2 |
| mtime |
20060913235959.9 |
| title
(primary) (eng) |
A Computationally Affordable Implementation of An Asymptotically Optimal BSS Algorithm for AR Sources |
| specification |
| page_count |
5 s. |
| media_type |
CD-ROM |
|
| serial |
| ARLID |
cav_un_epca*0076764 |
| title
|
Proceedings of 14th European Signal Processing Conference. EUSIPCO 2006 |
| page_num |
1-5 |
| publisher |
| place |
Florence |
| name |
EURASIP |
| year |
2006 |
|
|
| title
(cze) |
Vypocetne schudna implementace asymptoticky optimalniho algoritmu pro slepou separaci autoregresnich procesu |
| keyword |
independent component analysis |
| keyword |
blind source separation |
| author
(primary) |
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0213972 |
| name1 |
Doron |
| name2 |
E. |
| country |
IL |
|
| author
|
| ARLID |
cav_un_auth*0213973 |
| name1 |
Yeredor |
| name2 |
A. |
| country |
IL |
|
| author
|
| ARLID |
cav_un_auth*0213020 |
| name1 |
Nielsen |
| name2 |
Jan |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
| source_type |
datovy soubor |
| source_size |
212kB |
|
| COSATI |
12B |
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
The second-order blind identification (SOBI) algorithm for separation of stationary sources was proved to be useful in many biomedical applications. This paper revisits the so called weights-adjusted variant of SOBI, known as WASOBI, which is asymptotically optimal (in separating Gaussian parametric processes), yet prohibitively computationally demanding for more than 2-3 sources. A computationally feasible implementation of the algorithm is proposed, which has a complexity of the same order as SOBI. Excluding the estimation of the correlation matrices, the post-processing complexity of SOBI is $O(d^4M)$, where $d$ is the number of the signal components and $M$ is the number of covariance matrices involved. The additional complexity of our proposed implementation of WASOBI is $O(d^6+d^3M^3)$ operations. However, for WASOBI, the number $M$ of the matrices can be significantly lower than that of SOBI without compromising performance. WASOBI is shown to significantly outperform SOBI in simulation, and can be applied, e.g., in the processing of low density EEG signals. |
| abstract
(cze) |
Algoritmus SOBI je popularnim algortmem pro slepou separaci signalu, pouzivanym v biomedicine. Tento clanek se zabyva implementaci asymptoticky optimalni varianty tohoto algoritmu zname pod akronymem WASOBI. Je navrzena varianta tohoto algorimu ktera ma radove stejnou vypocetni narocnost jako puvodni algoritmus SOBI a umoznuje separaci 20 nezavislych zdroju v casovem horizontu minut. Je ukazana zlepsena presnost separace v porovnani s algoritmem SOBI. |
| action |
| ARLID |
cav_un_auth*0216569 |
| name |
European Signal Processing Conference. EUSIPCO /14./ |
| place |
Florence |
| dates |
04.09.2006-08.09.2006 |
| country |
IT |
|
| reportyear |
2007 |
| RIV |
BB |
| permalink |
http://hdl.handle.net/11104/0134655 |
| arlyear |
2006 |
| mrcbU56 |
datovy soubor 212kB |
| mrcbU63 |
cav_un_epca*0076764 Proceedings of 14th European Signal Processing Conference. EUSIPCO 2006 1 5 Florence EURASIP 2006 |
|