Pattern recognition and signal parameters extraction using machine learning methods

Abstract

Machine learning methods can be used for signal processing in different cases of physics research. A convolutional neural network was developed for the task of pulse counting in particle detectors for high energy physics. For the extraction of signal parameters was used a network with convolutional autoencoder architecture and a subsequent result reconstruction algorithm was developed and applied. A convolutional neural network was also developed for seismic studies with the task of identifying different events in seismograms. All of the algorithms with their architecture, input and output are presented and discussed.