A time domain blind source separation algorithm of convolutive sound mixtures is
studied based on a compact partial inversion formula in closed form. An L1-constrained minimization
problem is formulated to find demixing filter coefficients for source separation while capturing scaling
invariance and sparseness of solutions. The minimization aims to reduce (lagged) cross correlations
of the mixture signals, which are modeled stochastically. The problem is non-convex, however it
is put in a nonlinear least squares form where the robust and convergent Levenberg-Marquardt
iterative method is applicable to compute local minimizers. Efficiency is achieved in recovering
lower dimensional demixing filter solutions than the physical ones. Computations on recorded and
synthetic mixtures show satisfactory performance, and are compared with other iterative methods.
@article{1238158607,
author = {Liu, Jie and Xin, Jack and Qi, Yingyong and Zheng, Fan-Gang},
title = {A time domain algorithm for blind separation of convolutive sound mixtures and L1 constrainted minimization of cross correlations},
journal = {Commun. Math. Sci.},
volume = {7},
number = {1},
year = {2009},
pages = { 109-128},
language = {en},
url = {http://dml.mathdoc.fr/item/1238158607}
}
Liu, Jie; Xin, Jack; Qi, Yingyong; Zheng, Fan-Gang. A time domain algorithm for blind separation of convolutive sound mixtures and L1 constrainted minimization of cross correlations. Commun. Math. Sci., Tome 7 (2009) no. 1, pp. 109-128. http://gdmltest.u-ga.fr/item/1238158607/