Multiscale blind source separation

Blind wideband source separation

This paper deals with the general problem of separating two independent wideband sources when they are mixed by unknown filters. In order to solve this problem. a backward framework is proposed which is composed of two different stages. The fiist one consists of two linear predictors devoted to improve the source separation, whitening the input signals. Their coefficients are calculated applyin...

Blind Equalization via Blind Source Separation Techniques

This paper addresses the application of blind source separation (BSS) algorithms to the problem of blind equalization (BE) in a frequency selective multiuser environment. Compared with other algorithms that exploit the structural properties of the channel or data matrix, our approaches are insensitive to channel order estimation, robust to ill-conditioned channels and able to choose the \best" ...

Blind and semi-blind source separation

: a Blind Source Separation Technique

| Separation of sources consists in recovering a set of signals of which only instantaneous linear mixtures are observed. In many situations, no a priori information on the mixing matrix is available: the linear mixture should bèblindly' processed. This typically occurs in narrow-band array processing applications when the array manifold is unknown or distorted. This paper introduces a new sour...

Advances in Blind Source Separation

Blind source separation (BSS) and related topics such as independent component analysis (ICA), sparse component analysis (SCA), or nonnegative matrix factorization (NMF) have become emerging tools inmultivariate signal processing and data analysis and are now one of the hottest and emerging areas in signal processing with solid theoretical foundations and many potential applications. In fact, B...