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Principal Component Analysis

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Intensity Estimation of Spontaneous Facial Action Units Based on Their Sparsity Properties.

IEEE transactions on cybernetics
Automatic measurement of spontaneous facial action units (AUs) defined by the facial action coding system (FACS) is a challenging problem. The recent FACS user manual defines 33 AUs to describe different facial activities and expressions. In spontane...

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PloS one
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market tech...

Identification of a small set of plasma signalling proteins using neural network for prediction of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a dementia that gets worse with time resulting in loss of memory and cognitive functions. The life expectancy of AD patients following diagnosis is ∼7 years. In 2006, researchers estimated that 0.40% of the wor...

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PloS one
To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crosso...

The relationship between left ventricle myocardial performance index of healthy women and geographical factors.

International journal of biometeorology
The study focused on the relationship between geographical factors and left ventricular myocardial performance index (MPI)reference value, analyed the different distribution of MPI, and then provided a scientific basis for clinical examination. This ...

Automated classification of neurological disorders of gait using spatio-temporal gait parameters.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
OBJECTIVE: Automated pattern recognition systems have been used for accurate identification of neurological conditions as well as the evaluation of the treatment outcomes. This study aims to determine the accuracy of diagnoses of (oto-)neurological g...

Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes.

Physiological measurement
Patients suffering from atrial fibrillation can be classified into different subtypes, according to the temporal pattern of the arrhythmia and its recurrence. Nowadays, clinicians cannot differentiate a priori between the different subtypes, and pati...

An improved poly(A) motifs recognition method based on decision level fusion.

Computational biology and chemistry
Polyadenylation is the process of addition of poly(A) tail to mRNA 3' ends. Identification of motifs controlling polyadenylation plays an essential role in improving genome annotation accuracy and better understanding of the mechanisms governing gene...

Bridging the gap between motor imagery and motor execution with a brain-robot interface.

NeuroImage
According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially di...

Application of unfolded principal component analysis-radial basis function neural network for determination of celecoxib in human serum by three-dimensional excitation-emission matrix fluorescence spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study describes a simple and rapid approach of monitoring celecoxib (CLX). Unfolded principal component analysis-radial basis function neural network (UPCA-RBFNN) and excitation-emission spectra were combined to develop new model in the determin...