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Unsupervised, supervised, and reinforced learning via spiking computation

  • US 9,390,372 B2
  • Filed: 09/23/2014
  • Issued: 07/12/2016
  • Est. Priority Date: 09/16/2011
  • Status: Active Grant
First Claim
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1. A method for feature extraction, comprising:

  • providing sensory input to a first neural module in a neural network comprising a plurality of neural modules interconnected via a plurality of weighted synaptic connections;

    extracting one or more input features from said sensory input as said sensory input propagates from said first neural module through said neural network in a first direction via at least one of said plurality of weighted synaptic connections;

    providing motor output to a second neural module in said neural network;

    extracting one or more output features from said motor output as said motor output propagates from said second neural module through said neural network in a second direction via at least one of said plurality of weighted synaptic connections, wherein said first direction is opposite of said second direction; and

    associating said one or more input features with said one or more output features.

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