Tutorial on neural network applications in high energy physics [electronic resource] : A 1992 perspective

Published:: Washington, D.C. : United States. Dept. of Energy, 1992.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description:: 41 pages : digital, PDF file
Additional Creators:: Fermi National Accelerator Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information

Access Online

www.osti.gov

Availability

Finding items...

Restrictions on Access:

Free-to-read Unrestricted online access

Summary:

Feed forward and recurrent neural networks are introduced and related to standard data analysis tools. Tips are given on applications of neural nets to various areas of high energy physics. A review of applications within high energy physics and a summary of neural net hardware status are given.

Report Numbers:

E 1.99:fnal/c--92/121-e
E 1.99: conf-920172--7
conf-920172--7
fnal/c--92/121-e

Subject(s):

Other Subject(s):

Note:

Published through SciTech Connect.
04/01/1992.
"fnal/c--92/121-e"
" conf-920172--7"
"DE92016003"
"CDF/PUB/CDF/PUBLIC/1737"
2. international workshop on software engineering, artificial intelligence (AI), and neural nets for high energy and nuclear physics,L`Agelonde (France),13-18 Jan 1992.
Denby, B.

Funding Information:

AC02-76CH03000

View MARC record | catkey: 14063358