13 June 1995 Study and optimization of a neural network with fuzzy logic preprocessing for particle identification on a cosmic ray detector
Author Affiliations +
Abstract
A fuzzy logic preprocessing is used in connection with a back propagation neural network in particle recognition. As application on 4 GeV CERN experimental and Monte Carlo data of e- and (pi) (superscript -, taken with the prototype of the silicon Tungsten calorimeter of the Wizard collaboration, is shown. This preprocessing consists in giving as input to the net the membership value, for a given discriminating parameter value, to belong to a given particle class. In this way the input layer receives a normalized input. The net can then exploit the correlations between different parameters, resulting in an increased convergence speed and recognition capability of the net. Other advantages of this approach are its noise robustness and the simple generalization of other particle classes or energies.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marco Casolino, Marco Casolino, M. Candusso, M. Candusso, M. P. DePascale, M. P. DePascale, Aldo Morselli, Aldo Morselli, Piergiorgio Picozza, Piergiorgio Picozza, M. Ricci, M. Ricci, } "Study and optimization of a neural network with fuzzy logic preprocessing for particle identification on a cosmic ray detector", Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); doi: 10.1117/12.211797; https://doi.org/10.1117/12.211797
PROCEEDINGS
9 PAGES


SHARE
Back to Top