TY - GEN
T1 - Online Adaptive Quasi-Maximum Likelihood Blind Source Separation of Stationary Sources
AU - Weiss, Amir
AU - Yeredor, Arie
N1 - Publisher Copyright: © 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In the context of Blind Source Separation (BSS), we consider the problem of online separation of stationary sources. Based on the Maximum Likelihood (ML) solution for semi-blind separation of temporally-diverse Gaussian sources, and assuming that a parametric model of the sources' spectra is available, we propose an online adaptive Quasi-ML (QML) separation algorithm. The algorithm operates in an alternating fashion, updating at each iteration the (nuisance) spectra-characterizing parameters first, and then the demixing-matrix estimates, according to simple, computationally efficient update expressions which we derive. Our proposed algorithm, which leads to consistent separation of the sources, is demonstrated here, both analytically and empirically in a simulation experiment, for first-order autoregressive sources.
AB - In the context of Blind Source Separation (BSS), we consider the problem of online separation of stationary sources. Based on the Maximum Likelihood (ML) solution for semi-blind separation of temporally-diverse Gaussian sources, and assuming that a parametric model of the sources' spectra is available, we propose an online adaptive Quasi-ML (QML) separation algorithm. The algorithm operates in an alternating fashion, updating at each iteration the (nuisance) spectra-characterizing parameters first, and then the demixing-matrix estimates, according to simple, computationally efficient update expressions which we derive. Our proposed algorithm, which leads to consistent separation of the sources, is demonstrated here, both analytically and empirically in a simulation experiment, for first-order autoregressive sources.
KW - Blind source separation
KW - SeDJoCo
KW - independent component analysis
KW - quasi-maximum likelihood
UR - http://www.scopus.com/inward/record.url?scp=85063129688&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/icsee.2018.8646120
DO - https://doi.org/10.1109/icsee.2018.8646120
M3 - منشور من مؤتمر
T3 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
BT - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Y2 - 12 December 2018 through 14 December 2018
ER -