The problem of separation of audio sources recorded in a real world situation is well established in modern literature. A method to solve this problem is Blind Source Separation (BSS) using Independent Component Analysis (ICA). The recording environment is usually modeled as convolutive. Previous research on ICA of instantaneous mixtures provided solid background for the separation of convolved...

An important aspect of successfully analyzing data with blind source separation is to know the indeterminacies of the problem, that is how the separating model is related to the original mixing model. If linear independent component analysis (ICA) is used, it is well known that the mixing matrix can be found in principle, but for more general settings not many results exist. In this work, only ...

This paper describes our methods for repairing and restoring images of hidden paintings (paintings that have been painted over and are now covered by a new surface painting) that have been obtained via noninvasive X-ray fluorescence imaging of their canvases. This recently developed imaging technique measures the concentrations of various chemical elements at each two-dimensional spatial locati...

In this paper we present a new speaker-separation algorithm for separating signals with known statistical characteristics from mixed multi-channel recordings. Speaker separation has conventionally been treated as a problem of Blind Source Separation (BSS). This approach does not utilize any knowledge of the statistical characteristics of the signals to be separated, relying mainly on the indepe...

An l∞ norm based Source Separation Method has recently been introduced [1, 2], with the corresponding subgradient based algorithm that has a simple update rule. In this article, we propose a moving window modification to this algorithm, where instead of a long fixed window, a shorter length moving window is used. The simulation results for different blind source separation setups suggest that a...

The analysis and characterization of atrial tachyarrhythmias requires the previous estimation of the atrial activity (AA) free from any ventricular activity and other artefacts. This contribution considers a blind source separation (BSS) model to separate the AA from multilead electrocardiograms (ECGs). Previously proposed BSS methods for AA extraction exploit only the spatial diversity introdu...

This paper describes a method for solving the permutation problem in blind source separation (BSS) by frequencydomain independent component analysis (FD-ICA). FDICA is a well-known method for BSS of convolutive mixtures. However, FD-ICA has a source permutation problem, where estimated source components can become swapped at different frequencies. Many researchers have suggested methods to solv...