Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion because they have knowledge about normal heart contraction. This paper explores the potential of Independent Component Analysis (ICA) to extract local myocardial contractility patter...

The analysis and characterization of atrial fibrillation requires the previous extraction of the atrial activity from the electrocardiogram, where the independent atrial and ventricular activities are combined in addition to noise. An independent component analysis method is proposed where additional knowledge about the time and statistical structure of the sources is incorporated. Finally, a c...

In this paper we examine how the activation of one independent component analysis (ICA) feature changes first and second order statistics of other independent components in image patches. Essential for observing these dependencies is normalizing patch statistics, and selecting patches according to activation. We then estimate a model predicting the conditional statistics of a component using th...

In this paper we propose to use an instantaneous ICA method (BLUES) to separate the instruments in a real music stereo recording. We combine two strong separation techniques to segregate instruments from a mixture: ICA and binary time-frequency masking. By combining the methods, we are able to make use of the fact that the sources are differently distributed in both space, time and frequency. O...

A complex version of the Darmois–Skitovitch theorem is proved using a multivariate extension of the latter by Ghurye and Olkin. This makes it possible to calculate the indeterminacies of independent component analysis (ICA) with complex variables and coe4cients. Furthermore, the multivariate Darmois–Skitovitch theorem is used to show uniqueness of multidimensional ICA, where only groups of sour...

the brain – computer interface (bci) provides a communicational channel between human and machine. most of these systems are based on brain activities. brain computer-interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. the success of this methodology depends on the selection of methods to process the brain signals in each pha...

By investigating the possibility of plant species classification based on independent component analysis (ICA) for hyperspectral data with minor difference, the framework of a general plant species classification model that consists of ICA based data reduction, classifier training and verification is proposed in this paper. Five different types of discriminant analysis classifiers including Lin...

Saccades are conjunctive and believed to be the fastest eye movements, which function to redirect the fovea of the retina to the object of interest. Main sequence relations have generally been used for describing the dynamics of the saccadic eye movements. Fourier analysis has also been used in quantitative investigation of saccades. A previous investigation used an inverse method from the Four...

In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene expression time series data and compare their performance in clustering genes and in finding biologically meaningful modes. Up to now, only spatial ICA was applied to gene expression data analysis. However, in the case of...

Independent subspace analysis (ISA) that deals with multidimensional independent sources, is a generalization of independent component analysis (ICA). However, all known ISA algorithms may become ineffective when the sources possess temporal structure. The innovation process instead of the original mixtures has been proposed to solve ICA problems with temporal dependencies. Here we show that th...