Whereas most blind source separation (BSS) and blind mixture identification (BMI)
investigations concern linear mixtures (instantaneous or not), various recent works extended …

Blind source separation (BSS) is a generic signal processing problem. BSS methods aim to
estimate a set of unknown source signals, by using a set of available signals that are …

Visible, near-infrared and short wave infrared (VNIR/SWIR) hyperspectral imagery has
proven to be a useful technique for map** the soil surface properties over bare soils …

This book provides a detailed survey of the methods that were recently developed to handle
advanced versions of the blind source separation problem, which involve several types of …

The aim of our work is to quantify two gases (acetone and ethanol) diluted in an air buffer
using only a single metal oxide (MOX) sensor. We took advantage of the low selectivity of …

Digital documents are usually degraded during the scanning process due to the contents of
the backside of the scanned manuscript. This is often caused by the show-through effect, ie …

While most reported source separation methods concern linear mixtures, we here address
the nonlinear case. Even for a known nonlinear mixing model, creating a system which …

We proposed recently a new method for separating linear-quadratic mixtures of independent
real sources, based on parametric identification of a recurrent separating structure using an …

In this work, we propose a Bayesian source separation method of linear-quadratic (LQ) and
linear mixtures. Since our method relies on truncated prior distributions, it is particularly …

In this paper, we present a new method, formulated in a maximum-likelihood framework, for
blindly separating nonlinear mixtures of statistically independent signals. Our method …