In this paper we present an iterative inversion (II) approach to blind source separation (BSS). It consists of a quasi-Newton method for the resolution of an estimating equation obtained from the implicit inversion of a robust estimate of the mixing system. The resulting learning rule includes several existing algorithms for BSS as particular cases giving them a novel and unified interpretation...

been shown to solve the instantaneous BSS (Blind Source Separation) problem for temporally colored sources. In t h i s paper we show that arbitrary temporal filtering combined wi th models associated to the extension of standard P C A known as Oriented P C A (OPCA) provide a solution to the problem that is based on second order statist ics and requires no prewhitening of the observation signals...

In this paper we consider blind source separation (BSS) problem of signals which are spatially uncorrelated of order four, but temporally correlated of order four (for instance speech or biomedical signals). For such type of signals we propose a new sufficient condition for separation using fourth order statistics, stating that the separation is possible, if the source signals have distinct nor...

We consider blind receiver of (OFDM) system based on Blind Source Separation (BSS) adopting the ICA algorithm, which increases the spectral efficiency effectively compared to training based systems, and provides considerable performance enhancement over conventional training methods of detections. Several experiments were performed to verify the validity of the proposed ICA receiver. The (C-Fas...

When trying to understand the brain, it is of fundamental importance to analyse (e.g. from EEG/MEG measurements) what parts of the cortex interact with each other in order to infer more accurate models of brain activity. Common techniques like Blind Source Separation (BSS) can estimate brain sources and single out artifacts by using the underlying assumption of source signal independence. Howev...

This paper addresses the problem of blind multipleinput multiple-output deconvolution of a communication system. Two new iterative blind source separation (BSS) algorithms are presented, based on the minimization of multi-modulus criterion. Further, we show that the design of algorithm in the complex domain is quite complicated, so a special structure of real filtering matrix is suggested and m...

This thesis addresses the problems of blind source separation (BSS) and blind and semi-blind communications channel equalization. In blind source separation, signals from multiple sources arrive simultaneously at a sensor array, so that each sensor output contains a mixture of source signals. Sets of sensor outputs are processed to recover the source signals from the mixed observations. The ter...

Abstract The Electroencephalogram (EEG) signal is widely contaminated by a physiological artifact, such as muscle activity, heart rhythm, and eye movement. researcher has proposed number of methods to clean the EEG signal. A group these called Blind Source Separation (BSS). In this paper, we suggest an approach that combines BSS Discrete Wavelet Transform (DWT) algorithm, in order evaluate afte...

Harmonic separation plays an important role in power quality research due to the harmful impact to power system and electric apparatus. The accurate separation of harmonics is also the demand for filtering. This paper models the problem of harmonic separation as a blind source separation (BSS) task and the paper presents an algorithm called independent component analysis, which is widely used i...