On Computation of Approximate Joint Block-Diagonalization Using Ordinary AJD

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F12%3A00376329" target="_blank" >RIV/67985556:_____/12:00376329 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-28551-6_21" target="_blank" >http://dx.doi.org/10.1007/978-3-642-28551-6_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-28551-6_21" target="_blank" >10.1007/978-3-642-28551-6_21</a>

Result language
angličtina
Original language name
On Computation of Approximate Joint Block-Diagonalization Using Ordinary AJD
Original language description
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-diagonalizationis 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.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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