We consider the Blind Source Separation problem of linear mixtures with singular matrices and show that it can be solved if the sources are sufficiently sparse. More generally, we ...
We discuss a 3D spatial analysis of fMRI data taken during a combined word perception and motor task. The event - based experiment was part of a study to investigate the network of...
Ingo R. Keck, Fabian J. Theis, Peter Gruber, Elmar...
The blind separation problem where the sources are not independent, but have variance-dependencies is discussed. Hyv¨arinen and Hurri[1] proposed an algorithm which requires no as...
Abstract. We present a straightforward way to use temporal decorrelation as preprocessing in linear and post-nonlinear independent component analysis (ICA) with higher order statis...
The analysis and characterization of atrial tachyarrhythmias requires the previous estimation of the atrial activity (AA) free from any ventricular activity and other artefacts. Th...
Francisco Castells, Jorge Igual, Vicente Zarzoso, ...
The paper deals with blind source separation of images. The model which is adopted here is a convolutive multi-dimensional one. Recent results about polynomial matrices in several ...
This paper addresses the blind separation of noisy mixtures of independent sources. It discusses issues and techniques related to computing maximum likelihood estimates in Gaussian...
We address the blind source separation (BSS) problem for the convolutive mixing case. Second-order statistical methods are employed assuming the source signals are non-stationary a...
Different Computer Aided Diagnosis (CAD) systems have been recently developed to detect microcalcifications (MCs) in digitalized mammography, among other techniques, applying Gen...
We propose a relative optimization framework for quasi maximum likelihood blind deconvolution and the relative Newton method as its particular instance. Special Hessian structure a...
Alexander M. Bronstein, Michael M. Bronstein, Mich...