Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Clark S. Lindsey"'
Publikováno v:
JavaTech, an Introduction to Scientific and Technical Computing with Java: An Introduction to Scientific and Technical Computing with Java
Autor:
Clark S. Lindsey, Michael Strömberg
Publikováno v:
Pattern Recognition Letters. 21:265-268
We investigate using the frequency of simple features to provide image signatures for input to a classifier. In an approach inspired by the n-gram technique for text classification, a binary image is scanned with a small window, e.g. 3 × 3 matrix an
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 416:391-396
The possibility to extract the signal of high-mass gluino production in pp-interactions using the channel (jets+ p T miss ) is studied. The simulation includes a detailed modelling of gluino decay with mass m g =1000 GeV in the minimal supersymmetric
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 389:245-250
Biologically inspired image/signal processing, in particular neural networks like the Pulse-Coupled Neural Network (PCNN), are revisited. Their use with high granularity high-energy physics detectors, as well as optical sensing devices, for filtering
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 389:251-254
In this paper we discuss the use of massively parallel hardware for data mining. An introduction to the concept is followed by some benchmark results.
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 385:361-365
We examine four hardware neural network systems with tests of simulated trigger data from a high energy experiment. The hardware systems include both analog and digital design and implement different neural network architectures and training algorith
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 381:502-507
This paper presents the implementation of the Dynamic Decay Adjustment (DDA) algorithm in a CNAPS parallel computer system having 128 processing nodes. The DDA algorithm has several inherent advantages, and the implementation of it in the CNAPS syste
Publikováno v:
IFAC Proceedings Volumes. 29:7470-7473
In the present paper we suggest the use of artificial neural networks in hardware for the use with star trackers on satellites. In particular micro-satellites should benefit from this low weight solution. Other features of the approach is the redunda
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 368:855-858
The approach of using a conventional neural network as well as one utilizing the O-algorithm are compared in an application of particle tracking. In the latter case we control the confidence level of the results, which is a major advantage when the n
Publikováno v:
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 356:498-506
The present investigation uses information from computer simulations to train neural networks to identify decays of heavy Higgs particles (mH ⪢ mz). Results are presented both for software and hardware analog neural networks. The hardware tests inc