Application of a Kohonen network classifier in TeV -ray astronomy
Abstract:A Kohonen type unsupervised artificial neural network has been used to increase the sensitivity of the atmospheric Cherenkov imaging technique used in ground-based TeV -ray astronomy. The network classifies Cherenkov events as -induced or hadron-induced on the basis of their spatial frequency components. When used in conjunction with the established Supercuts classifier it increases the sensitivity of the technique by .
Document Type: Miscellaneous
Publication date: December 1, 1998