0376329 20240111140815.720120911235959.9 10.1007/978-3-642-28551-6_21 9 s. C cav_un_epca*0376325978-3-642-28550-9163-171HeidelbergSpringer2012TheisFabian joint block diagonalization independent subspace analysis cav_un_auth*0101212 Tichavský Petr Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0213973 Yeredor A. IL cav_un_auth*0108100 Koldovský Zbyněk Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2012/SI/tichavsky-on computation of approximate joint block-diagonalization using ordinary ajd.pdf 443kB 1M0572 GA MŠk cav_un_auth*0001814 GA102/09/1278 GA ČR cav_un_auth*0253174 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. cav_un_auth*0280771 Latent Variable Analysis and Signal Separation,10th International Conference, LVA/ICA 2012 Tel Aviv 12.03.2012-15.03.2012 IL 2013 BB 3 PO RVO:67985556 http://hdl.handle.net/11104/0208759 2012 443kB 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 Theis Fabian 340