189 research outputs found
Discriminating signal from background using neural networks. Application to top-quark search at the Fermilab Tevatron
The application of Neural Networks in High Energy Physics to the separation
of signal from background events is studied. A variety of problems usually
encountered in this sort of analyses, from variable selection to systematic
errors, are presented. The top--quark search is used as an example to
illustrate the problems and proposed solutions.Comment: 11 pages, 3 figures, psfi
Enhancing the top signal at Tevatron using Neural Nets
We show that Neural Nets can be useful for top analysis at Tevatron. The main
features of and background events on a mixed sample are projected in
a single output, which controls the efficiency and purity of the
signal.Comment: 11 pages, 6 figures (not included and available from the authors),
Latex, UB-ECM-PF 94/1
Discriminating signal from background using neural networks: Application to top-quark search at the Fermilab Tevatron
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