Optimal linear feature transformations for semi-continuous hidden Markov models
نویسندگان
چکیده
Linear discriminant or Karhunen-Lo eve transforms are established techniques for mapping features into a lower dimensional subspace. This paper introduces a uniform statistical framework, where the computation of the optimal feature reduction is formalized as a Maximum-Likelihood estimation problem. The experimental evaluation of this suggested extension of linear selection methods shows a slight improvement of the recognition accuracy.
منابع مشابه
Optimal Linear Feature Transformations Forsemi - Continuous Hidden Markov
Linear discriminant or Karhunen-Lo eve transforms are established techniques for mapping features into a lower dimensional subspace. This paper introduces a uniform statistical framework, where the computation of the optimal feature reduction is formalized as a Maximum-Likelihood estimation problem. The experimental evaluation of this suggested extension of linear selection methods shows a slig...
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