SOBI is a blind source separation algorithm based on time decorrelation. It uses multiple time autocovariance matrices, and performs joint diagonalization thus being more robust th...
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
A series of recent results shows that if a signal admits a sufficiently sparse representation (in terms of the number of nonzero coefficients) in an “incoherent” dictionary, th...
This paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when the number of source signals is large, and the potential sou...
Abstract. In this paper, the authors address the permutation ambiguity that exists in frequency domain Independent Component Analysis of convolutive mixtures. Many methods have bee...
Abstract. Most ICA algorithms are sensitive to outliers. Instead of robustifying existing algorithms by outlier rejection techniques, we show how a simple outlier index can be used...
Frank C. Meinecke, Stefan Harmeling, Klaus-Robert ...
Abstract. Mutual information (MI) is a common criterion in independent component analysis (ICA) optimization. MI is derived from probability density functions (PDF). There are scen...
Sarit Shwartz, Michael Zibulevsky, Yoav Y. Schechn...
In this paper, we consider independence property between a random process and its first derivative. Then, for linear mixtures, we show that cross-correlations between mixtures and...
Sebastien Lagrange, Luc Jaulin, Vincent Vigneron, ...
Abstract. Frequency domain ICA has been used successfully to separate the utterances of interfering speakers in convolutive environments, see e.g. [6],[7]. Improved separation resu...
We treat the problem of Blind Deconvolution of Single Input - Single Output (SISO) systems with real or complex binary sources. We explicate the basic mathematical idea by focusing...
Konstantinos I. Diamantaras, Theophilos Papadimitr...