Identification of Near Fault Pulse Shaped Signals With Machine Learning Algorithms

Conventional imaging with inactive repetition times (TR) between two successive excitation pulses is highly inefficient, especially when using se- quences with long scan times and

The sampler simulated in the third chapter is based on nonlinear interaction (polarization rotation induced by XPM) in optical fiber between the signal to be resolved and a

The study of the time response of a CsI(Tl) scintilla- tor to ions of different type and energy has shown that the light decay can be reasonably well fit by two ex- ponential

signal and the elements of the basis allows to select the shape that is more similar and this in turn determines the that is more similar and this in turn determines the

PSA algorithms developed for highly segmented HPGe detectors make use of a signal data base which contains the detector pulse shapes for all the possible interaction positions

Gamma ray tracking arrays composed of large volume segmented HPGe detectors like AGATA and GRETA will be used in experiments with radioactive ion beams.. The gamma

This study represents a crucial test of the AGATA detectors for the measurement of high-energy gamma rays, in terms of detection efficiency, energy resolution, tracking and

The Pulse Shape Comparison based Scan (PSCS) method allows to decrease the time consumption needed to perform such detector characterization measurements. It has been described