Oja et al. [11] and Ollila et al. [12] showed that, under general assumptions, any two scatter matrices with the so called independent components property can be used to estimate the unmixing matrix for the independent component analysis (ICA). The method is a generalization of Cardoso’s [2] FOBI estimate which uses the regular covariance matrix and a scatter matrix based on fourth moments. Different choices of the two scatter matrices are compared in a simulation study. Based on the study, we recommend always the use of two robust scatter matrices. For possible asymmetric independent components, symmetrized versions of the scatter matrix estimates should be used
Independent Component Analysis (ICA) is the problem of learning a square matrix A, given samples of ...
ABSTRACT: Independent component analysis (ICA, see, e.g., Hyvarinen, et al., 2001) is a technique of...
International audience<p>Independent component analysis (ICA) and blind source separation (BSS) deal...
In independent subspace analysis (ISA) one assumes that the components of the observed random vecto...
Independent Component Analysis (ICA) is a statistical method for transforming multidimensional rando...
A new method for separating the mixtures of independent sources has been proposed recently in [Oja e...
Independent Component Analysis (ICA) recently has attracted much attention in the statistical litera...
<div><p>Independent component analysis (ICA) recently has attracted much attention in the statistica...
Independent Components Analysis finds a linear transformation to variables which are maximally stati...
Independent component analysis is a relatively new computational technique for finding hidden compon...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
Independent Components Analysis (ICA) is a blind source separation method that has been developed to...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
The Independent Component Analysis (ICA) of a random vector consists of searching for the linear tra...
Independent Component Analysis (ICA) is the problem of learning a square matrix A, given samples of ...
ABSTRACT: Independent component analysis (ICA, see, e.g., Hyvarinen, et al., 2001) is a technique of...
International audience<p>Independent component analysis (ICA) and blind source separation (BSS) deal...
In independent subspace analysis (ISA) one assumes that the components of the observed random vecto...
Independent Component Analysis (ICA) is a statistical method for transforming multidimensional rando...
A new method for separating the mixtures of independent sources has been proposed recently in [Oja e...
Independent Component Analysis (ICA) recently has attracted much attention in the statistical litera...
<div><p>Independent component analysis (ICA) recently has attracted much attention in the statistica...
Independent Components Analysis finds a linear transformation to variables which are maximally stati...
Independent component analysis is a relatively new computational technique for finding hidden compon...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
Independent Components Analysis (ICA) is a blind source separation method that has been developed to...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
Procedures such as FOBI that jointly diagonalize two matrices with the independence property have a ...
The Independent Component Analysis (ICA) of a random vector consists of searching for the linear tra...
Independent Component Analysis (ICA) is the problem of learning a square matrix A, given samples of ...
ABSTRACT: Independent component analysis (ICA, see, e.g., Hyvarinen, et al., 2001) is a technique of...
International audience<p>Independent component analysis (ICA) and blind source separation (BSS) deal...