| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0376329 |
| utime |
20240111140815.7 |
| mtime |
20120911235959.9 |
| DOI |
10.1007/978-3-642-28551-6_21 |
| title
(primary) (eng) |
On Computation of Approximate Joint Block-Diagonalization Using Ordinary AJD |
| specification |
| page_count |
9 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0376325 |
| ISBN |
978-3-642-28550-9 |
| title
|
Latent Variable Analysis and Signal Separation |
| page_num |
163-171 |
| publisher |
| place |
Heidelberg |
| name |
Springer |
| year |
2012 |
|
| editor |
|
|
| keyword |
joint block diagonalization |
| keyword |
independent subspace analysis |
| author
(primary) |
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| 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*0213973 |
| name1 |
Yeredor |
| name2 |
A. |
| country |
IL |
|
| author
|
| ARLID |
cav_un_auth*0108100 |
| name1 |
Koldovský |
| name2 |
Zbyněk |
| 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 |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
GA102/09/1278 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0253174 |
|
| abstract
(eng) |
Approximate joint block diagonalization (AJBD) of a set of matrices has applications in blind source separation, e.g., when the signal mixtures contain mutually independent subspaces of dimension higher than one. The main message of this paper is that certain ordinary approximate joint diagonalization (AJD) methods can also be used successfully for AJBD, but not all are suitable equally well. In particular, we prove that when the set is exactly jointly block-diagonalizable, perfect block-diagonalization is attainable by the recently proposed AJD algorithm “U-WEDGE" (uniformly weighted exhaustive diagonalization with Gaussian iteration) - but this basic consistency property is not shared by some other popular AJD algorithms. In addition, we show using simulation, that in the more general noisy case, the subspace identification accuracy of U-WEDGE compares favorably to competitors. |
| action |
| ARLID |
cav_un_auth*0280771 |
| name |
Latent Variable Analysis and Signal Separation,10th International Conference, LVA/ICA 2012 |
| place |
Tel Aviv |
| dates |
12.03.2012-15.03.2012 |
| country |
IL |
|
| reportyear |
2013 |
| RIV |
BB |
| num_of_auth |
3 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0208759 |
| arlyear |
2012 |
| mrcbU56 |
443kB |
| mrcbU63 |
cav_un_epca*0376325 Latent Variable Analysis and Signal Separation 978-3-642-28550-9 163 171 Heidelberg Springer 2012 Lecture Notes on Computer Science 7191 |
| mrcbU67 |
Theis Fabian 340 |
|