| abstract |
The invention relates to a new method for the detection and classification of non-periodic signals and to the system that implements same, in the field 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 machine learning techniques, such as ANN (Artificial Neural Networks) (2), to an input signal, in order 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). |