blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is...

We present a multiple antenna system for industrial, scientific, and medical (ISM)-band transmission (MASI). The hardware demonstrator was developed and realized at our institute. It enables multiple-input multiple-output (MIMO)-communication applications and is capable of transmiting arbitrary signals using 8 transmit and 8 receive antennas in parallel. It operates in the 2.4GHz ISM-band. The ...

We address the problem of blind source separation in the underdetermined mixture case. Two statistical tests are proposed to reduce the number of empirical parameters involved in standard sparsenessbased underdetermined blind source separation (UBSS) methods. The first test performs multisource selection of the suitable time-frequency points for source recovery and is full automatic. The second...

A class of methods based on multichannel linear prediction (MCLP) can achieve effective blind dereverberation of a source, when the source is observed with a microphone array. We propose an inventive use of MCLP as a pre-processing step for blind source separation with a microphone array. We show theoretically that, under certain assumptions, such pre-processing reduces the original blind rever...

This paper deals with the problem of Blind Source Separation. Contrary to the vast majority of works, we do not assume the statistical independence betwwen sources and explicitly consider that they are dependent. We introduce three particular models of dependent sources and show that their cumulants have interesting properties. Based on these properties, we investigate the behaviour of classica...

One of the most important problems in frequency domain blind source separation is the inconsistency across frequency in the permutation of the source estimates. In this paper we present a new algorithm that simultaneously diagonalizes the intrafrequency and the inter-frequency correlation matrices of the source estimates. Experimental results, using speech signals, reveal that the algorithm ach...

This paper deals with the blind source separation problem in convolutive mixtures when the sources are colored processes. In this case, classical methods first extract the innovation processes of the sources and then color them, which yields two successive filter approximations. On the contrary, we propose here a new concept allowing to directly extract estimates of the colored sources in one s...

Source separation by cepstral smoothing of binary masks In this paper, we propose a separation system of speech signals from two convolutive mixtures. The suggested system is based on the combination of blind source separation technique with a time-frequency masking procedure, followed by a smoothing cepstral. Indeed, after separation of signal sources, the estimated binary masks undergo a ceps...