Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Workshop Applied Methods of Statistical Analysis Nonparametric Methods in Cybernetics and System Analysis, AMSA 2017; Красноярск, Россия; Красноярск, Россия

Год издания: 2017

Ключевые слова: Differential equation of dynamic object, Nonparametric identification, Object with memory, The selection of essential variables

Аннотация: The problem of constructing the parametric structure of dynamic object is analyzed. The method of determining the structure of the dynamic differential equation with up to parameters is based on the application of the rule of allocation of significant variables for nonparametric identification. The article deals with the non-parametric model of dynamic objects. The relationship of coefficient blur kernel function and the influence of a particular variable, mea- sured in non-parametric model output object is investigate. The algorithm of identification of the structure of the difference equation of the dynamic object includes the steps of finding the optimal coefficients blur kernel function for each variable sampling rates, elimination of the unimportant variables, modeling and simulation calculation of the relative error. © Novosibirsk State Technical University, 2017.

Журнал: Applied Methods of Statistical Analysis. Nonparametric methods in cybernetics and system analysis (AMSA'2017)

Номера страниц: 115-119

ISSN журнала: 2313870X

Издатель: Novosibirsk State Technical University

• Raskina A.V. (Siberian Federal University, Krasnoyarsk, Russian Federation)

• Scopus
• Ядро РИНЦ (eLIBRARY.RU)