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Automation and Remote Control

, Volume 62, Issue 4, pp 580–589 | Cite as

Statistical Recognition of Multivariate Non-Gaussian Patterns

  • V. S. Mukha
Article
  • 24 Downloads

Abstract

Statistical recognition of multivariate patterns is investigated for the case in which the attribute vectors of patterns have non-Gaussian distributions and only the moments of these distributions are known. A recognition approach based on the approximation of pattern distributions by Gram–Charlier series and use of the Bayes decision rule is developed. New decision rules are designed. A computer-aided modeling experiment is described.

Keywords

Mechanical Engineer Pattern Distribution Modeling Experiment System Theory Decision Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© MAIK “Nauka/Interperiodica” 2001

Authors and Affiliations

  • V. S. Mukha
    • 1
  1. 1.Belarussian State University of Informatics and RadioelectronicsMinskBelarus

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