Nay Laguna | Universidad Autonoma del Estado de Hidalgo (original) (raw)

Papers by Nay Laguna

Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 1992

The usual methods of automatic radiation spectra analysis, based on fittings of peaks and backgro... more The usual methods of automatic radiation spectra analysis, based on fittings of peaks and background to exact mathematical curves, are valid for high resolution detectors. However, these methods are less successful for lower resolution detectors, such as the common scintillators or new room temperature semiconductors . Trying to solve some of the problems inherent in the application of complex fittings to the response of these detectors, we test here a new and less strict approach, based on the use of a neural network algorithm known as "associative memory". This method appears useful in those cases in which a simple operation and a fast response are needed, together with a reasonable (and not extreme) accuracy. Furthermore, as the pattern recognition is carried out through the rough shape of the whole spectrum, instead of each individual peak, it can be used with advantage for low resolution detectors. With the idea of comparing the behavior of this method with the "classical" ones, the response of the network in the analysis of several spectra, taken with a Nal spectrometer, is presented.

Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 1992

The usual methods of automatic radiation spectra analysis, based on fittings of peaks and backgro... more The usual methods of automatic radiation spectra analysis, based on fittings of peaks and background to exact mathematical curves, are valid for high resolution detectors. However, these methods are less successful for lower resolution detectors, such as the common scintillators or new room temperature semiconductors . Trying to solve some of the problems inherent in the application of complex fittings to the response of these detectors, we test here a new and less strict approach, based on the use of a neural network algorithm known as "associative memory". This method appears useful in those cases in which a simple operation and a fast response are needed, together with a reasonable (and not extreme) accuracy. Furthermore, as the pattern recognition is carried out through the rough shape of the whole spectrum, instead of each individual peak, it can be used with advantage for low resolution detectors. With the idea of comparing the behavior of this method with the "classical" ones, the response of the network in the analysis of several spectra, taken with a Nal spectrometer, is presented.