Abstract. We proposed recently a new method for separating linearquadratic mixtures of independent real sources, based on parametric identification of a recurrent separating struc...
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...
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient FastICA (EFICA) offers an ...