In this paper, we review recent advances in blind source separation (BSS) and independent
component analysis (ICA) for nonlinear mixing models. After a general introduction to BSS …

The smoothness of graph signals has found desirable real applications for processing
irregular (graph-based) signals. When the latent sources of the mixtures provided to us as …

In this paper, a nonparametric “gradient” of the mutual information is first introduced. It is
used for showing that mutual information has no local minima. Using the introduced …

This paper provides fast algorithms to perform independent component analysis based on
the mutual information criterion. The main ingredient is the binning technique and the use of …

During oil and gas exploration, it is difficult to quantitatively evaluate fluid components and
accurately calculate the saturation of different fluids because of the overlapping of fluid …

The smoothness of the graph signals on predefined/constructed graphs appears in many
natural applications of processing unstructured (ie, graph-based) data. In the case of latent …

This paper addresses blind source separation in convolutive post nonlinear (CPNL)
mixtures. In these mixtures, the sources are mixed convolutively, and then measured by …

In this paper, we address the problem of blind compensation of nonlinear distortions. Our
approach relies on the assumption that the input signal is bandlimited. We then make use of …

The development of chemical sensor arrays based on Blind Source Separation (BSS)
provides a promising solution to overcome the interference problem associated with Ion …

In this paper we propose a blind source separation method to process the data acquired by
an array of ion-selective electrodes in order to measure the ionic activity of different ions in …