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Statistical Recognition of Multivariate Non-Gaussian Patterns

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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.

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  1. Belarussian State University of Informatics and Radioelectronics, Minsk, Belarus

    V. S. Mukha

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  1. V. S. Mukha
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Mukha, V.S. Statistical Recognition of Multivariate Non-Gaussian Patterns. Automation and Remote Control 62, 580–589 (2001). https://doi.org/10.1023/A:1010281528189

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