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 analysis, from variable selection to systematic errors, are presented. The top-quark search is used as an example to illustrate the problems and proposed solutions.
- Received 7 July 1995
DOI:https://doi.org/10.1103/PhysRevD.54.1233
©1996 American Physical Society