Title :
DESPRIT - histogram based blind source separation of more sources than sensors using subspace methods
Author :
Rickard, Scott ; Melia, Thomas ; Fearon, Conor
Author_Institution :
Deigital Signal Process. Res. Group, Dublin Coll. Univ.
Abstract :
A blind source separation (BSS) technique is presented which combines the subspace processing and associated DOA capability of ESPRIT with the weighted histogram of DUET. The method allows for a weakened version of the disjoint signal assumption of DUET and can be seen as a natural extension of DUET to more than two mixtures. Instead of only allowing at most one source be active at any time-frequency point, up to M-1 sources can be active where M is the number of anechoic mixtures. The combination of these techniques creates a DUET-ESPRIT (DESPRIT) blind source separation algorithm which can demix an arbitrary number of sources N, even when N > M
Keywords :
blind source separation; matrix algebra; parameter estimation; anechoic mixtures; disjoint signal assumption; estimation of signal parameter via rotational invariance techniques; histogram based blind source separation; subspace methods; Array signal processing; Blind source separation; Delay estimation; Digital signal processing; Direction of arrival estimation; Histograms; Microphone arrays; Signal processing algorithms; Source separation; Time frequency analysis;
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on
Conference_Location :
New Paltz, NY
Print_ISBN :
0-7803-9154-3
DOI :
10.1109/ASPAA.2005.1540154