Approximation of double-dimensional distribution laws of dependent random variables
Автор: Kudryavtsev Dmitry, Lyozin Ilya
Журнал: Известия Самарского научного центра Российской академии наук @izvestiya-ssc
Рубрика: Автоматизированные системы научных исследований
Статья в выпуске: 4-2 т.16, 2014 года.
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Article is dedicated to the approximation problem of double dimensional dependent random variables. Solution of the problem and ability neural networks usage is introduced in it. Distribution type is determined by a multi-layer perceptron, and parameters are calculated by RBF-network. As a result, formulas for computing parameters of double dimensional densities of probability are derived. The article represents a table with the research methods results.
Double dimensional random variable, approximation of the density of probability, parametric model, neural network
Короткий адрес: https://sciup.org/148203202
IDR: 148203202
