Arkhipov A.I., Glazunov N.M., Khyzhniak À.V.
Heuristic criterion for class recognition by spectral brightness

The authors consider the problem of recognition of a class of objects by the results of multispectral measurements (spectral brightness of signals) and available spectral and statistical characteristics of the given classes. On the basis of probabilistic and statistical considerations, as well as quantization of continuous distributions, the heuristic recognition criterion is proposed. Based on the criterion, the heuristic method of recognition is presented. Modifications of the method are proposed to improve its reliability and efficiency. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: alternative hypothesis, class of recognition objects, discrete distribution, heuristic recognition criteria, multivariate density, normal distribution, probability density function, standard deviation, variance, Luminance, Normal distribution, Probability density function, Probability distributions, Alternative hypothesis, class of recognition objects, Discrete distribution, Heuristic recognition, Multivariate density, Standard deviation, variance, Heuristic methods

Cite:
Arkhipov A.I., Glazunov N.M., Khyzhniak À.V. (2018). Heuristic criterion for class recognition by spectral brightness. Cybernetics and Systems Analysis, 54 (1), 105-110. doi: https://doi.org/10.1007/s10559-018-0010-7 http://jnas.nbuv.gov.ua/article/UJRN-0000805861 [In Russian].