Method for operating a neural network with missing and/or incomplete data

  • US 5,842,189 A
  • Filed: 09/27/1997
  • Issued: 11/24/1998
  • Est. Priority Date: 11/24/1992
  • Status: Expired due to Term
First Claim
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1. A method for estimating error in a prediction output space of a predictive system model over a prediction input space as a prediction error, comprising the steps of:

  • receiving an input vector comprising a plurality of input values that occupy the prediction input space;

    outputting an output prediction error vector that occupies an output space corresponding to the prediction output space of the predictive system model;

    mapping the prediction input space to the prediction output space through a representation of the prediction error in the predictive system model to provide the output prediction error vector in the step of outputting;

    receiving an unprocessed data input vector having associated therewith unprocessed data, the unprocessed data input vector associated with substantially the same input space as the input vector, the unprocessed data input vector having errors associated with the associated unprocessed data in select portions of the prediction input space; and

    processing the unprocessed data in the unprocessed data vector to minimize the errors therein to provide the input vector on an output.

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