METHOD FOR DETECTION AND CLASSIFICATION OF NON-PERIODIC SIGNALS AND THE RESPECTIVE SYSTEM THAT IMPLEMENTS IT

A new method is described for the detection and classification of non-periodic signals and the respective system that implements it, within the scope of flow cytometry techniques for the acquisition of biological information in order to increase the accuracy in the detection of labeling particles.This is achieved through the use of classifiers of the composed or independent type (20), which apply to an input signal (1) machine learning techniques, such as ANN (Artificial Neural Networks) (2), to execute a new detection methodology that combines the filtering and decision steps, as a way to classify non-periodic signals at the output of the classifier (3).