×

NOISE-ENHANCED CONVOLUTIONAL NEURAL NETWORKS

  • US 20160019459A1
  • Filed: 07/20/2015
  • Published: 01/21/2016
  • Est. Priority Date: 07/18/2014
  • Status: Active Grant
First Claim
Patent Images

1. A learning computer system that estimates parameters and states of a stochastic or uncertain system comprising a data processing system that includes a hardware processor that has a configuration that:

  • receives data from a user or other source;

    processes the received data through layers of processing units, thereby generating processed data;

    applies masks or filters to the processed data using convolutional processing;

    processes the masked or filtered data to produce one or more intermediate and output signals;

    compares the output signals with reference signals to generate error signals;

    sends and processes the error signals back through the layers of processing units;

    generates random, chaotic, fuzzy, or other numerical perturbations of the received data, the processed data, or the output signals;

    estimates the parameters and states of the stochastic or uncertain system using the received data, the numerical perturbations, and previous parameters and states of the stochastic or uncertain system;

    determines whether the generated numerical perturbations satisfy a condition; and

    if the numerical perturbations satisfy the condition, injects the numerical perturbations into the estimated parameters or states, the received data, the processed data, the masked or filtered data, or the processing units.

View all claims
  • 1 Assignment
Timeline View
Assignment View
    ×
    ×