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Method and system for selecting pattern recognition training vectors

  • US 5,796,924 A
  • Filed: 03/19/1996
  • Issued: 08/18/1998
  • Est. Priority Date: 03/19/1996
  • Status: Expired due to Term
First Claim
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1. In a computer, a method of selecting a plurality of training vectors for a pattern recognition system, the method comprising the following steps:

  • receiving a plurality of example signals representing a plurality of classes within an example space, each of the plurality of example signals being associated with a respective class;

    defining a plurality of clusters, each of the plurality of clusters being associated with one of the plurality of classes;

    assigning the plurality of example signals to the plurality of clusters as a function of a plurality of cluster-example distances;

    determining whether at least one decision boundary needs greater definition, if so, increasing in number the plurality of clusters and repeating the step of assigning;

    selecting the plurality of training vectors by sampling of the plurality of example signals from each of the plurality of clusters; and

    fitting a polynomial expansion to the plurality of training vectors using a least squares estimate, wherein the polynomial expansion has a form ##EQU3## wherein x represents at least one element of a training vector, i, j, and n are integers, y represents a discriminant signal, a0 represents a zero-order coefficient, bi represents a first-order coefficient, and cij represents a second-order coefficient.

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