Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers

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Abstract

<jats:p>Oscillation of cerebral blood flow (CBF) in physiological or pathophysiological brain states is common, therefore it is promising to identify cerebral circulation disorders based on CBF signal classification. To characterize temporal blood flow patterns, we applied two feature extractions, spectral matrix and wavelet subband analysis. To distinguish between different physiological states, two different classifications have been developed - the radial basis function-based neural network and a support vector classifier with a Gaussian kernel. Feature extraction and classification are evaluated and their efficiency compared. Calculation was done using Mathematica 5.1 and its Wavelet Application.</jats:p>

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