You need JavaScript to view this
ETDEWEB   /       /    Controlled neural network application in track-match problem

Controlled neural network application in track-match problem

Technical Report:

SAVE / SHARE

XML RIS EndNote CSV/Excel JSON

Abstract

Track-match problem of high energy physics (HEP) data handling is formulated in terms of incidence matrices. The corresponding Hopfield neural network is developed to solve this type of constraint satisfaction problems (CSP). A special concept of the controlled neural network is proposed as a basis of an algorithm for the effective CSP solution. Results of comparable calculations show the very high performance of this algorithm against conventional search procedures. 8 refs.; 1 fig.; 1 tab.
Authors:
Publication Date:
Dec 31, 1993
Product Type:
Technical Report
Report Number:
JINR-E-10-93-415
Reference Number:
SCA: 990200; PA: AIX-25:032113; EDB-94:073085; NTS-94:020634; SN: 94001192755
Resource Relation:
Other Information: PBD: 1993
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; NEURAL NETWORKS; CONTROL; PARTICLE TRACKS; ALGORITHMS; MATRICES; TOPOLOGY; WEIGHTING FUNCTIONS; 990200; MATHEMATICS AND COMPUTERS
OSTI ID:
10144870
Research Organizations:
Joint Inst. for Nuclear Research, Dubna (Russian Federation). Lab. of Computing Techniques and Automation
Country of Origin:
JINR
Language:
English
Other Identifying Numbers:
Other: ON: DE94622703; TRN: XJ9406280032113
Availability:
OSTI; NTIS (US Sales Only); INIS
Submitting Site:
INIS
Size:
7 p.
Announcement Date:
Jul 05, 2005

Technical Report:

SAVE / SHARE

XML RIS EndNote CSV/Excel JSON

Citation Formats

Baginyan, S A, and Ososkov, G A. Controlled neural network application in track-match problem. JINR: N. p., 1993. Web.
Baginyan, S A, & Ososkov, G A. Controlled neural network application in track-match problem. JINR.
Baginyan, S A, and Ososkov, G A. 1993. "Controlled neural network application in track-match problem." JINR.
@misc{etde_10144870,
title = {Controlled neural network application in track-match problem}
 author = {Baginyan, S A, and Ososkov, G A}
 abstractNote = {Track-match problem of high energy physics (HEP) data handling is formulated in terms of incidence matrices. The corresponding Hopfield neural network is developed to solve this type of constraint satisfaction problems (CSP). A special concept of the controlled neural network is proposed as a basis of an algorithm for the effective CSP solution. Results of comparable calculations show the very high performance of this algorithm against conventional search procedures. 8 refs.; 1 fig.; 1 tab.}
 place = {JINR}
 year = {1993}
 month = {Dec}
 }