Published 1990 | Version v1
Report Restricted

Applications of neural networks in high energy physics

Creators

  • 1. Brown Univ., Providence, RI (USA)
  • 2. Zeller Research Ltd., Bristol, RI (USA)

Description

Neural network techniques provide promising solutions to pattern recognition problems in high energy physics. We discuss several applications of back propagation networks, and in particular describe the operation of an electron algorithm based on calorimeter energies. 5 refs., 5 figs., 1 tab

Availability note (English)

MF available from INIS under the Report Number; NTIS, PC A02/MF A01 as DE90013325; OSTI; INIS; US Govt. Printing Office Dep.

Files

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Additional details

Publishing Information

Imprint Pagination
9 p.
Report number
DOE/ER/03130--52

Conference

Title
Computing in high energy physics.
Dates
9-13 Apr 1990.
Place
Santa Fe, NM (USA).

INIS

Country of Publication
United States
Country of Input or Organization
United States
INIS RN
21073697
Subject category
S72: PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; S99: GENERAL AND MISCELLANEOUS;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; ELECTRONS; HIGH ENERGY PHYSICS; NEURAL NETWORKS; PATTERN RECOGNITION; SHOWER COUNTERS
Descriptors DEC
ELEMENTARY PARTICLES; FERMIONS; LEPTONS; MEASURING INSTRUMENTS; PHYSICS; RADIATION DETECTORS

Optional Information

Contract/Grant/Project number
Contract AC02-76ER03130
Secondary number(s)
COO--3130TC-52; CONF-9004190--13.