Application of a Neural Network Approach to Measurements of Cosmic Ray Fluxes

A neural network approach for processing the output data from a spectrometer with diamond detectors on a spacecraft is discussed. A mathematical apparatus for obtaining differentiable data on fluxes of electrons, protons, and heavy charged particles in 21 energy bands is proposed.

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Bibliographic Details
Published in:Measurement techniques 2016-06, Vol.59 (3), p.293-302
Main Authors: Istratov, A. Yu, Zakharchenko, K. V., Kaperko, A. F., Kolyubin, V. A., Kulagin, V. P., Kurochkin, R. I.
Format: Article
Language:English
Subjects:
Analytical Chemistry
Characterization and Evaluation of Materials
Charged particles
Cosmic rays
Detectors
Diamonds
Energy
Energy bands
Fluxes
Mathematical analysis
Mathematical models
Measurement
Measurement Science and Instrumentation
Measurement techniques
Neural networks
Physical Chemistry
Physics
Physics and Astronomy
Protons
Radiation
Sensors
Spacecraft
Spectrometers
Studies
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Description
Summary:A neural network approach for processing the output data from a spectrometer with diamond detectors on a spacecraft is discussed. A mathematical apparatus for obtaining differentiable data on fluxes of electrons, protons, and heavy charged particles in 21 energy bands is proposed.
ISSN:0543-1972
1573-8906
DOI:10.1007/s11018-016-0961-x