Identification of b jets using neural networks
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Abstract The problem of identifying b quark jets produced at LEP using a neural network technique has been studied. We find that networks perform better separation if they are given simple inputs, as opposed to inputs already combined into variables believed to be good for separation. Some first studies of systematic errors resulting from using neural network separation techniques are given.
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