Abstract. In this paper, we investigate the importance of the high frequencies in the problem of convolutive blind source separation (BSS) of speech signals. In particular, we focu...
The paper deals with blind source separation of images. The model which is adopted here is a convolutive multi-dimensional one. Recent results about polynomial matrices in several ...
We consider the problem of convolutive blind source separation of stereo mixtures. This is often tackled using frequency-domain independent component analysis (FDICA), or time-fre...
Maria G. Jafari, Emmanuel Vincent, Samer A. Abdall...
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Becau...
Antti Honkela, Stefan Harmeling, Leo Lundqvist, Ha...
In underdetermined blind source separation problems, it is common practice to exploit the underlying sparsity of the sources for demixing. In this work, we propose two sparse decom...