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Measurement Techniques

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19-08-2019 | GENERAL PROBLEMS OF METROLOGY AND MEASUREMENT TECHNIQUE

Methods for Rapid Selection of Kernel Function Blur Coefficients in a Nonparametric Pattern Recognition Algorithm

Authors: A. V. Lapko, V. A. Lapko

Published in: Measurement Techniques | Issue 4/2019

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Abstract

A fast algorithm is proposed for choosing the coefficients of blur coefficients for kernel functions in a nonparametric estimate of the separating surface equation for a two-alternative pattern recognition problem. The algorithm is based on the results of a study of the asymptotic properties of nonparametric estimates of the decision function in the recognition problem for patterns and the probability densities of the distribution of random variables in classes. We compare the proposed algorithm with the traditional approach based on minimizing the estimated probability of a classification error.

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Title: Methods for Rapid Selection of Kernel Function Blur Coefficients in a Nonparametric Pattern Recognition Algorithm
Authors: A. V. Lapko
V. A. Lapko
Publication date: 19-08-2019
Publisher: Springer US
Published in: Measurement Techniques / Issue 4/2019
Print ISSN: 0543-1972
Electronic ISSN: 1573-8906
DOI: https://doi.org/10.1007/s11018-019-01621-1

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