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This paper presents a dysphonic voice classification system using the wavelet packet transform and the best basis algorithm (BBA) as dimensionality reductor and 06 artificial neural networks (ANN) acting as specialist systems. Each ANN was a 03-layer multilayer perceptron with 64 input nodes, 01 output node and in the intermediary layer the number of(More)
This study aims at applying algorithms for the spectral estimation and the classification of EEG signals during imaginary movements. Accordingly, it was used a database created by Graz University of Technology for the BCI Competition II. The database was created through an experiment in which an individual was asked to imagine the movement of her right or(More)
BACKGROUND Several studies have analyzed the correlation between digital and standard videotape echocardiographic images. The advantages of digital echocardiography are a faster exam, lower costs and a greater number of exams performed. Our study's aim was to evaluate the correlation and agreement between cardiac dimensions measured by M-mode and(More)
The aim of this work is to investigate quantitatively the capability of the Continuous Wavelet Transform (CWT) as a tool to estimate (calculate) Jitter and Shimmer, assessing the error between these indices calculated in each Wavelet decomposition and the ones for the original signal, for several dilatation levels. Two synthetic vowels /a/ were generated(More)
A new class of wavelet functions called data-based autocorrelation wavelets is developed for analyzing Magnetic Resonance Spectroscopic (MRS) signals by means of the continuous wavelet transform (CWT), instead of the traditional wavelet like Morlet wavelet. These new wavelets are derived from the normalized autocorrelation function from metabolite data and(More)
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