QUARK FLAVOR SENSITIVITY OF THE MAMMALIAN CORTEX

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Abstract
Most applications of Neural Networks in High Energy Physics have involved the use of simple backpropagation or learning vector quantization networks on offline data sets with relatively low dimensionality. In the present work we raise the question of whether ideas drawn from the current understanding of animal nervous systems can be used to build trigger systems for use on raw high energy physics data of high dimensionality. The problem of a secondary vertex trigger is chosen as an illustrative example.

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