An important element of learning from examples is the extraction of patterns and regularities from data. This paper investigates the structure of patterns in data defined over discrete features, i.e. features with two or more qualitatively distinct values. Any such pattern can be algebraically decomposed into a spectrum of component patterns, each of which is a simpler or more atomic ‘‘regulari...

We consider here surf zone turbulence measurements, recorded in the Eastern English Channel using a sonic anemometer. In order to characterize the intermittent properties of their fluctuations at many time scales, we analyze the experimental time series using the Empirical Mode Decomposition (EMD) method. The series is decomposed into a sum of modes, each one narrow-banded, and we show that som...

Due to abundant spectral information contained in the hyperspectral images, they are suitable data for anomalous targets detection. The use of spatial features in addition to spectral ones can improve the anomaly detection performance. An anomaly detector, called nonparametric spectral-spatial detector (NSSD), is proposed in this work which utilizes the benefits of spatial features and local st...

purpose: to assess three main emotions (happy, sad and calm) by various classifiers, using appropriate feature extraction and feature selection. materials and methods: in this study a combination of power spectral density and a series of statistical features are proposed as statistical-frequency features. next, a feature selection method from pattern recognition (pr) tools is presented to extra...

This paper investigates the extent of tiger (Panthera tigris) vocal individuality through both qualitative and quantitative approaches using long distance roars from six individual tigers at Omaha's Henry Doorly Zoo in Omaha, NE. The framework for comparison across individuals includes statistical and discriminant function analysis across whole vocalization measures and statistical pattern clas...

Spectral features from specific regions in infrared spectra of organic molecules can consistently be attributed to certain functional groups. Artificial neural networks were employed as a pattern recognition tool to elucidate the relationships between functional groups and spectral features. The ability of these network models to predict the presence and absence of a variety of functional group...

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as ind...

This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the m...