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UNSUPERVISED, SUPERVISED AND REINFORCED LEARNING VIA SPIKING COMPUTATION

  • US 20180268294A1
  • Filed: 05/18/2018
  • Published: 09/20/2018
  • Est. Priority Date: 09/16/2011
  • Status: Active Grant
First Claim
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1. A method comprising:

  • receiving output generated by a neuron population of a neural network;

    determining whether the output is a false negative or a false positive; and

    self-tuning the neural network by;

    providing the output to a first set of neuron populations of the neural network in response to determining the output is a false negative, wherein the output is learned as the output propagates through the first set of neuron populations; and

    providing the output to a second set of neuron populations of the neural network in response to determining the output is a false positive, wherein the output is unlearned as the output propagates through the second set of neuron populations.

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