1990
DOI: 10.1109/23.106627
|View full text |Cite
|
Sign up to set email alerts
|

Neural networks for triggering

Abstract: Tao types of neural network beauty trigger architecturn, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment.The efficiencin for B's and rejection of background obtained are encouraging.lf hardware tcsk arc mccesaful, the dectron identification archikcturc will be tated in the 1991 run of CDF.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
8
0

Year Published

1991
1991
1993
1993

Publication Types

Select...
7
2

Relationship

2
7

Authors

Journals

citations
Cited by 20 publications
(9 citation statements)
references
References 6 publications
0
8
0
Order By: Relevance
“…The particles from the hadronized b quark jet deposit hadronic and electromagnetic energy in a few towers and the underlying minimum bias event normally deposits much less than 0.5 GeV per tower. Our procedure for triggering on the b -> evX decay is to look for central electromagnetic (CEM) calorimeter trigger towers that pass a certain E t threshold (seed towers) [5] . The signals from the seed tower and from We obtain optimal weight and bias values for S via a minimization procedure which tries to separate signal from background patterns .…”
Section: B -Evx Application Of Neural Nets At Ppmentioning
confidence: 99%
“…The particles from the hadronized b quark jet deposit hadronic and electromagnetic energy in a few towers and the underlying minimum bias event normally deposits much less than 0.5 GeV per tower. Our procedure for triggering on the b -> evX decay is to look for central electromagnetic (CEM) calorimeter trigger towers that pass a certain E t threshold (seed towers) [5] . The signals from the seed tower and from We obtain optimal weight and bias values for S via a minimization procedure which tries to separate signal from background patterns .…”
Section: B -Evx Application Of Neural Nets At Ppmentioning
confidence: 99%
“…Neural networks have been proposed as an adjunct to or even replacement for cuts traditionally employed to separate signal from background in high-energy experiments. 1 Certainly the development of a powerful, general training algorithm for non-recursive neural networks 2 has established the forward-feed, back-propagation neural network as an important tool for pattern recognition, both in artificial intelligence and industrial applications. * A neural network can be trained to distinguish "signal" events from "background" events in a high-energy collider, differentiating between the two on the basis of kinematical variables such as angular separation, missing transverse energy / E T , etc.…”
Section: Introductionmentioning
confidence: 99%
“…one could easily experiment with different isolation cuts. Also, a B trigger system is already in piace that uses the Intel chip [4,5,6]. (There is also a central calorimeter isolation trigger similar to the plug isolation trigger but it simply cuts on the sum oi"the outer tower energies rather than on the ratio of outer to inner[2].)…”
Section: Introductionmentioning
confidence: 99%