Track finding with neural networks

Carsten Peterson

doi:10.1016/0168-9002(89)91300-4

Track finding with neural networks

Research output: Contribution to journal › Article › peer-review

Abstract

A neural network algorithm for finding tracks in high energy physics experiments is presented. The performance of the algorithm is explored on modest size samples with encouraging results. It is inherently parallel and thus suitable for execution on a conventional SIMD architecture. More important, it naturally lends itself to direct implementations in custom made hardware, which would permit real time operations and hence facilitate fast triggers. Both VLSI and optical technology implementations are briefly discussed.

Original language	English
Pages (from-to)	537-545
Number of pages	9
Journal	Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment
Volume	279
Issue number	3
DOIs	https://doi.org/10.1016/0168-9002(89)91300-4
Publication status	Published - 1989 Jul 15

Subject classification (UKÄ)

Other Physics Topics

Access to Document

10.1016/0168-9002(89)91300-4

Cite this

@article{1601b7421d174e79b4114d381365086c,

title = "Track finding with neural networks",

abstract = "A neural network algorithm for finding tracks in high energy physics experiments is presented. The performance of the algorithm is explored on modest size samples with encouraging results. It is inherently parallel and thus suitable for execution on a conventional SIMD architecture. More important, it naturally lends itself to direct implementations in custom made hardware, which would permit real time operations and hence facilitate fast triggers. Both VLSI and optical technology implementations are briefly discussed.",

author = "Carsten Peterson",

year = "1989",

month = jul,

day = "15",

doi = "10.1016/0168-9002(89)91300-4",

language = "English",

volume = "279",

pages = "537--545",

journal = "Nuclear Instruments \& Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment",

issn = "0168-9002",

publisher = "Elsevier",

number = "3",

}

TY - JOUR

T1 - Track finding with neural networks

AU - Peterson, Carsten

PY - 1989/7/15

Y1 - 1989/7/15

N2 - A neural network algorithm for finding tracks in high energy physics experiments is presented. The performance of the algorithm is explored on modest size samples with encouraging results. It is inherently parallel and thus suitable for execution on a conventional SIMD architecture. More important, it naturally lends itself to direct implementations in custom made hardware, which would permit real time operations and hence facilitate fast triggers. Both VLSI and optical technology implementations are briefly discussed.

AB - A neural network algorithm for finding tracks in high energy physics experiments is presented. The performance of the algorithm is explored on modest size samples with encouraging results. It is inherently parallel and thus suitable for execution on a conventional SIMD architecture. More important, it naturally lends itself to direct implementations in custom made hardware, which would permit real time operations and hence facilitate fast triggers. Both VLSI and optical technology implementations are briefly discussed.

UR - https://www.scopus.com/pages/publications/0024701127

U2 - 10.1016/0168-9002(89)91300-4

DO - 10.1016/0168-9002(89)91300-4

M3 - Article

AN - SCOPUS:0024701127

SN - 0168-9002

VL - 279

SP - 537

EP - 545

JO - Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment

JF - Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment

IS - 3

ER -

Track finding with neural networks

Abstract

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Cite this