First results on characterization of Cherenkov images through combined useof Hillas, fractal and wavelet parameters

Based on Monte Carlo simulations using the CORSIKA code, it is shown that C herenkov images produced by ultrahigh energy gamma-rays and cosmic ray nucl ei (proton, Neon and Iron) are fractal in nature. The resulting multifracta l and wavelet moments when employed in association with the conventional Hi llas parameters as inputs to a properly-trained artificial neural network a re found to provide a more efficient primary characterization scheme than t he one based on the use of Hillas or fractal parameters alone. (C) 1999 Els evier Science B.V. All rights reserved.