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Data processing at the SSC with structured neural networks

Lackner, Klaus S ; Sandberg, Vernon D ; Sharp, David H

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Título:
Data processing at the SSC with structured neural networks
Autor: Lackner, Klaus S ; Sandberg, Vernon D ; Sharp, David H
Assuntos: 46 Instrumentation Related To Nuclear Science And Technology ; 99 General And Miscellaneous//Mathematics, Computing, And Information Science ; 990200 ; Data Processing ; High Energy Physics Instrumentation ; Mathematics & Computers ; Measuring Instruments ; Neural Networks ; Particle Tracks ; Pattern Recognition ; Processing ; Radiation Detectors ; Radiation Instrumentation ; Shower Counters ; Storage Rings 440104 ; Superconducting Super Collider
Notas: Symposium on detector research and development for the Superconducting Super Collider, Fort Worth, TX (USA), 15-18 Oct 1990
Descrição: SSC detectors will place extreme demands on data processing systems. One must reduce the data flux to manageable proportions at the earliest possible stage. This observations has led us to emphasize low-level data processing and track reconstruction. We report progress in three areas: A network compiler has been designed which generates programmable and trainable tree-structured nets; algorithms for track reconstruction have been designed and implemented in such nets; exploratory studies have been made on the use of such nets to carry out low-level processing on hardware components of a central detector. 6 refs., 1 fig.
Editor: Los Alamos National Laboratory
Data de criação/publicação: 1990-01
Idioma: Inglês

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