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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN 印刷: 1064-2315
ISSN オンライン: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v43.i4.20
pages 11-19

Adaptive Models of Signal Approximation in Structural-Parametric Classes of Functions

Fedor G. Garashchenko
Kyiv National Taras Shevchenko University, Kyiv, Ukraine
Olga F. Shvets
Kiev National Taras Shevchenko University, Ukraine
Olga S. Degtyar
Kiev National Taras Shevchenko University, Ukraine

要約

Adaptive models of signal approximation in structural-parametric classes of functions were proposed. Approximation is done by means of iteration procedure in the form of system of ordinary differential equations. Software-algorithmic application was verified on test examples and real problems, which confirms the efficiency of the suggested approach.


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