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NEURAL NETWORK AND METHOD OF NEURAL NETWORK TRAINING
专利权人:
Progress, Inc.
发明人:
Pescianschi Dmitri
申请号:
US201715449614
公开号:
US2017177998(A1)
申请日:
2017.03.03
申请国别(地区):
美国
年份:
2017
代理人:
摘要:
A neural network includes inputs for receiving input signals, and synapses connected to the inputs and having corrective weights organized in an array. Training images are either received by the inputs as an array or codified as such during training of the network. The network also includes neurons, each having an output connected with at least one input via one synapse and generating a neuron sum array by summing corrective weights selected from each synapse connected to the respective neuron. Furthermore, the network includes a controller that receives desired images in an array, determines a deviation of the neuron sum array from the desired output value array, and generates a deviation array. The controller modifies the corrective weight array using the deviation array. Adding up the modified corrective weights to determine the neuron sum array reduces the subject deviation and generates a trained corrective weight array for concurrent network training.
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