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Artificial neural network that mimics real neurons by incorporate the concept of time, in which neurons fire when its potential reaches a target value.
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.