Russian
нейросеть Portuguese
rede neural artificial Spanish
red neural artificial Catalan
xarxa neuronal artificial 
Computational model used in machine learning, based on connected, hierarchical functions.
Russian
импульсная нейронная сеть Portuguese
modelos de disparos neuronais Spanish
red neuronal de impulsos Artificial neural network that mimics real neurons by incorporate the concept of time, in which neurons fire when its potential reaches a target value.
Spanish
red neuronal estocastica Independent television station in Sarasota, Florida, United States.
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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.
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The interplay between miR-491-3p and SNN was evaluated through dual luciferase reporter gene assay.
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The performance of the on-chip training SNN system is validated through MNIST data set classification based on network size and total time step.
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We found out that SNN was the pairing target of miR-491-3p and result showed that miR-491-3p and SNN interacted with each other.
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We also found out that the effects of miR-491-3p were in Rb cells were almost entirely canceled out at the overexpression of SNN.
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The SNN systems achieve accuracy of 97.83% with 1 hidden layer and 98.44% with 4 hidden layers in fully connected neural networks.
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