When a parameter space has a certain underlying structure, the ordinary gradient of a
function does not represent its steepest direction, but the natural gradient does. Information …

The paper considers an application of blind identification to beamforming. The key point is to
use estimates of directional vectors rather than resort to their hypothesised value. By using …

We introduce a novel fast algorithm for independent component analysis, which can be used
for blind source separation and feature extraction. We show how a neural network learning …

With solid theoretical foundations and numerous potential applications, Blind Signal
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …

Source separation consists of recovering a set of independent signals when only mixtures
with unknown coefficients are observed. This paper introduces a class of adaptive …

The blind separation of sources is a recent and important problem in signal processing.
Since 1984, it has been studied by many authors whilst many algorithms have been …

Blind source separation consists of recovering a set of signals of which only instantaneous
linear mixtures are observed. Thus far, this problem has been solved using statistical …

We propose two methods for separating mixture of independent sources without any precise
knowledge of their probability distribution. They are obtained by considering a maximum …

We address the problem of separation of mutually independent sources in nonlinear
mixtures. First, we propose theoretical results and prove that in the general case, it is not …

In this paper, we address the adaptive blind source separation of independent sources
using higher order statistics. Although this problem was considered in numerous works …