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...

We present a system for source separation from monaural musical mixtures based on sinusoidal modeling and on a library of timbre models trained a priori. The models, which rely on Principal Component Analysis, serve as time-frequency probabilistic templates of the spectral envelope. They are used to match groups of sinusoidal tracks and assign them to a source, as well as to reconstruct overlap...

The authors address the identification of predominant music instruments in polytimbral audio by previously dividing the original signal into several streams. Several strategies are evaluated, ranging from low to high complexity with respect to the segregation algorithm and models used for classification. The dataset of interest is built from professionally produced recordings, which typically p...

Spectrogram factorization methods have been proposed for single channel source separation [1–4], audio analysis [5–8] and more recently multichannel source separation [9–11]. All spectrogram factorization approaches incorrectly assume that the mixture spectrogram is the sum of the source spectrograms. In fact, the mixture spectrogram depends on the source spectrograms and the phase difference b...

Under-determined mixtures are characterized by the fact that they have more inputs than outputs, or, with the antenna array processing terminology, more sources than sensors. The problem addressed is that of identifying and inverting the mixture, which obviously does not admit a linear inverse. Identification is carried out with the help of tensor canonical decompositions. On the other hand, th...

Astrometric accuracy of complex modern VLBI arrays cannot be calculated analytically. We study the astrometric accuracy of phasereferenced VLBI observations for the VLBA, EVN and global VLBI array by simulating VLBI data for targets at declinations −25◦, 0◦, 25◦, 50◦, 75◦ and 85◦. The systematic error components considered in this study are calibrator position, station coordinate, Earth orienta...

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...

Blind signal separation (BSS) is an emerging signal processing technique, aiming at recovering unobserved signals or`sources' from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption of mutual independence between the signals. The weakness of the assumptions makes it a powerful approach but requires to venture beyond familiar second order statistics....

The problem of the blind signal separation (BSS) consists of estimating the latent component signals in a linear mixture, referred to as the sources, starting from several observed signals, without relying on any specific knowledge of the sources. In particular, when the sources are audible, this problem is known as to the cocktail-party problem, making reference to the ability of the human ear...