Title :
Kink recognition with neural networks
Author :
Stimpfl-Abele, G.
Author_Institution :
Univ. Blaise Pascal, Aubiere, France
Abstract :
The task of finding decays of charged tracks inside a tracking device is divided into two parts. First, a neural network is used to recognize kinks in well-constructed tracks. The inputs to this classification network are the residuals and the curvature obtained by a one-track fit. If a kink has been found, the same inputs are fed into a second neural network, which gives the radial position of the decay vertex. Both algorithms use feedforward nets with error backpropagation. Very good performance is found in comparison with conventional methods
Keywords :
feedforward neural nets; pattern recognition; physics computing; position sensitive particle detectors; proportional counters; charged tracks; classification network; decay vertex; error backpropagation; feedforward nets; kink recognition; neural networks; one-track fit; radial position; track decays; tracking device; Discrete event simulation; Feedforward systems; Mesons; Monte Carlo methods; Neural networks; Pattern recognition;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1992., Conference Record of the 1992 IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-0884-0
DOI :
10.1109/NSSMIC.1992.301445