Blind separation with Gaussian mixture model for convolutively mixed sources
Masashi Ohata, Toshiharu Mukai, Kiyotoshi Matsuoka · 2004
This paper proposes an online blind separation algorithm with Gaussian mixture model for convolutively mixed sources. Although similar algorithms were proposed, they were derived for independent and identically distributed (iid) sources. They may not work for sources which are not made iid by any linear filter. From the theoretical viewpoint, our algorithm also works well for the sources and search for an optimal separator simultaneously, it can be applied to the case where their statistical properties are quite unknown, except that sources are nonGaussian.