Title :
Neural network approach to process jet fragmentation information
Author :
Dong, Dawei ; Gyulassy, Miklos
Author_Institution :
Lawrence Berkeley Lab., California Univ., Berkeley, CA, USA
Abstract :
Recent progress on the development and applications of novel neurocomputing techniques for pattern recognition problems of relevance to nuclear experiments is reviewed. A high-pass neural filter was developed for jet analysis. The weights of the neural filter were learned by error propagation of a simulated nuclear reaction. It is shown that the method recovered the primordial jet distribution to a surprising high degree of accuracy
Keywords :
digital filters; high-pass filters; jets; neural nets; nuclear fragmentation; nuclear reactions and scattering; pattern recognition; physics computing; error propagation; high-pass neural filter; neural filter weights; nuclear experiments; pattern recognition; primordial jet distribution; process jet fragmentation information; Artificial neural networks; Biological neural networks; Cyclotrons; Detectors; Filters; Information processing; Laboratories; Neural networks; Neurons; Pattern recognition;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227171
