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Apparatus and methods for training in convolutional neural networks

  • US 10,643,129 B2
  • Filed: 10/29/2018
  • Issued: 05/05/2020
  • Est. Priority Date: 04/29/2016
  • Status: Active Grant
First Claim
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1. An apparatus for backpropagation of a convolutional neural network, comprising:

  • a master computation circuit configured to;

    receive input data, andselect one or more portions of the input data based on a predetermined convolution window in response to an instruction; and

    one or more slave computation circuits respectively configured to convolute one of the one or more portions of the input data with one of one or more calculated first data gradients to generate a kernel gradient,wherein the master computation circuit is further configured to update a prestored convolution kernel based on the kernel gradient,wherein the one or more slave computation circuits are respectively configured to multiply at least a portion of the prestored convolution kernel with the one or more first data gradients, andwherein the master computation circuit is further configured to calculate one or more second data gradients based on a derivative of an activation function and a sum of one or more multiplication results between the first data gradients and the portion of the prestored convolution kernel.

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