In this paper, the performances of appearance-based statistical methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) are tested and compared for the recognition of colored face images. Three sets of experiments are conducted for relative performance evaluations. In the first set of experiments, the recognition performanc...

This communication aims at giving some insights into the use of Independent Component Analysis (ICA) for solving biomedical problems. First the concept of ICA is reviewed and different classes of ICA methods are described. Next a survey on most encountered biomedical problems solved using ICA is detailed. Finally a comparative performance study of thirteen ICA algorithms is performed on biomedical

The intracranial internal carotid artery (ICA) is a muscular artery and lacks external elastic lamina (EEL). Stenosis of the intracranial ICA is relatively uncommon, but the most common site is the cavernous portion. The characteristics of the arterial wall structures were examined using serial 3-mm sections of 32 intracranial ICAs obtained from 50 cadavers to identify where the EEL disappeared...

We propose source-space independent component analysis (ICA) for separation, tomography, and time-course reconstruction of EEG and MEG source signals. Source-space ICA is based on the application of singular value decomposition and ICA on the neuroelectrical signals from all brain voxels obtained post minimum-variance beamforming of sensor-space EEG or MEG. We describe the theoretical backgroun...

OBJECTIVE The clinical significance of an intramural course (or bridging) of the coronary artery remains controversial. We investigated the relationship between intramural coronary arteries (ICAs) and coronary stenosis and prognosis of subjects with ICA. METHODS AND RESULTS ICA and coronary stenosis were assessed by multidetector computed tomography coronary angiography. ICAs in the left ante...

In this paper a new method is proposed based on the combination of ICA (Imperial Competitive Algorithm) and GA (Genetic Algorithm) which improves the convergence speed and accuracy of the optimization results. The new algorithm, which is named R-ICA-GA (RecursiveICA-GA), runs ICA and GA consecutively. It is shown that a fast decrease occurs while the proposed algorithm switches from ICA to GA. ...

Full-duplex communications systems that transmit and receive simultaneously suffer self-interference due to the mixing of transmitted signal weaker received at same node. The problem becomes compounded in Multi-Input Multi-Output (MIMO) systems, where considerable overhead is dedicated training. In this article, we discuss using blind source separation techniques, namely Independent Component A...

Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. In some applications, it is preferable to extract only one desired source signal instead of all source signals, and this can be achieved by a one-unit ICA technique. ICA with reference (ICA-R) is a one-unit ICA algor...

Permutation ambiguity of the classical ICA may cause problems in feature extraction for pattern classification. To solve that, we include a selective prior for de-mixing coefficients into the classical ICA. Since the prior is constructed upon the classification information from the training data, we refer to the proposed ICA model with a selective prior as a supervised ICA. We formulate the lea...