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In this paper, it is presented an automated classification based on S-transform as feature extraction tool and Decision Tree as algorithm classifier. The signals generated according to mathematical models, including complex disturbances, have been used to design and test this approach, where noise is added to the signals from 40dB to 20dB. Finally, several disturbances, simple and complex, have been...
An automated classification based on S-transform as feature extraction tool and Artificial Neural Network as algorithm classifier is presented. The signals generated according to mathematical models have been used to obtain experimental results in two stages, first, with a data set with only simple disturbances and, later, including complex disturbances, more usual in real electrical systems. In both...
An automated classification system based on Wavelet transform as a feature extraction tool in combination with Artificial Neural Network as algorithm classifier is presented. Perturbed signals generated according to mathematical models have been used to obtain experimental results in two stages, first, with a data set with simple disturbances and, later, including complex disturbances, more usual...
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