Title of article :
Particle identification by multifractal parameters in γ-astronomy with the HEGRA-Cherenkov-telescopes
Author/Authors :
Schنfer، نويسنده , , B.M. and Hofmann، نويسنده , , W. and Lampeitl، نويسنده , , H. and Hemberger، نويسنده , , M.، نويسنده ,
Pages :
10
From page :
394
To page :
403
Abstract :
Cherenkov images of air showers can also be classified using multifractal and wavelet parameters, as compared to the conventional Hillas image parameters. This new technique was applied to the images recorded by the cameras of the stereoscopic imaging air Cherenkov-telescopes operated by the HEGRA collaboration. With respect to the identification of particles, the performance of multifractal and wavelet parameters was examined using a data sample from the observation of the active galaxy Mkn 501 that showed a high γ-ray flux. The multifractal parameters were also combined with the Hillas parameters using a neural network approach in order to further improve the γ/hadron-separation.
Keywords :
?/hadron-separation , wavelets , NEURAL NETWORKS , Imaging air Cherenkov-technique , Multifractal parameters
Journal title :
Astroparticle Physics
Record number :
2015216
Link To Document :
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