Discriminating signal from background using neural networks. Application to top-quark search at the Fermilab Tevatron
arXiv:hep-ph/9603269 · doi:10.1103/PhysRevD.54.1233
Abstract
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.
11 pages, 3 figures, psfig