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Pattern recognition scheme using probabilistic models based on mixtures distribution of discrete distribution

  • US 6,064,958 A
  • Filed: 09/19/1997
  • Issued: 05/16/2000
  • Est. Priority Date: 09/20/1996
  • Status: Expired due to Fees
First Claim
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1. A pattern recognition method, comprising the steps of:

  • calculating a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and

    outputting a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result.

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