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Stochastic neural networks are a type of artificial neural networks built by introducing random variations into the network, either by giving the network's neurons stochastic transfer functions, or by giving them stochastic weights.
SNN was born in the Eastern Cape town of Bizana, in 1996.
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Results: One hundred percent of the SNs were identified with our SNNS method.
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Four peptides constituting the model were selected by supervised neural network algorithm (SNN).
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In addition, the impact of device variations on the performance of the on-chip training SNN system is evaluated.
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To train SNNs with supervision, we propose an efficient on-chip training scheme approximating backpropagation algorithm suitable for hardware implementation.