USE OF NEURAL NETS TO MEASURE THE τ POLARIZATION AND ITS BAYESIAN INTERPRETATION
1991 ◽
Vol 02
(03)
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pp. 221-228
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Keyword(s):
We have tested a neural network (NN) technique as a method to determine the helicity of the τ particles in the process: e+e−→(Z0, γ*)→τ+τ−→(ρν)(ρν). It takes into account in a natural way the fact that both taus have different helicity and gives efficiencies comparable to the Bayesian method. We have found this “academic” example a nice way to introduce the analytical interpretation of the net output, showing that these neural nets techniques are equivalent to a Bayesian Decision Rule.
2019 ◽
Vol 8
(9S2)
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pp. 263-268
Keyword(s):
2004 ◽
Vol 98
(2)
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pp. 371-378
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2020 ◽
Vol 29
(05)
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pp. 2050011
Keyword(s):
2000 ◽
Vol 36
(1)
◽
pp. 176-188
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Keyword(s):
Keyword(s):