Evaluation of neural classifiers using statistic methods for identification of laryngeal pathologies

The use of statistical elements, like nonparametric tests and principal components analysis, allows the evaluation of the behavior and the performance of artificial neural networks when acoustical measurements are used to identify larynx diseases from which patterns are naturally overlapped. In this work, techniques to improve the results of neural network through the manipulation of the training patterns and convergence control will be discussed.

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