Application of a neural network simulation to the modelling of the COMPTEL background.

Details Application of a neural network simulation to the modelling of the COMPTEL background. Application of a neural network simulation to the modelling of the COMPTEL background.

Dec 1996

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996a%26as..120c.699v&link_type=abstract

Astronomy and Astrophysics Supplement, v.120, p.699-702

Astronomy and Astrophysics

Astrophysics

Gamma-Rays: Observations, Atmospheric Effect, Instrumentation: Detectors

Scientific paper

COMPTEL onboard the Compton Gamma Ray Observatory (CGRO) measures gamma-rays in the background dominated energy range from 750keV to 30MeV. The event rate of the background varies strongly with orbital parameters, such as cut-off rigidity, position of the earth in the field of view and location of the spacecraft above the earth. Some, but not all, parameters can be modelled with analytic functions. A Neural Network Simulation with two hidden layers of 24 neurons each, ten input neurons and one output neuron, was applied to the data. For the training of the Neural Network an error backpropagation algorithm was used. The resulting model was tested on an independent dataset, and the relative importance of the orbital parameters on the background model was derived.

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