Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ http://cyberleninka....arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Некоторые замечания к h-моделям безынерционных процессов с запаздыванием

Некоторые замечания к h-моделям безынерционных процессов с запаздыванием

Abstract

Исследуется проблема моделирования дискретно-непрерывных процессов, имеющих «трубчатую» структуру в пространстве входных-выходных переменных. Моделирование процессов этого класса существенно отличается от общепринятых параметрических моделей, представляющих собой поверхности в том же пространстве. При построении обучающихся параметрических моделей «трубчатых» процессов необходимо использование соответствующих непараметрических индикаторов. Рассмотрены некоторые частные примеры моделирования «трубчатых» процессов, из которых следует, что процессы протекают в пространствах дробной размерности. Приводится случай функции многих переменных и анализируется ситуация, когда с течением времени эти переменные могут «исчезать» и «возникать» вновь. Показано, что вычисление размерности дробного пространства может осуществляться различными путями.

The paper examines the modeling problem of discrete-continuous processes with a “tubular” structure in the space of the “input-output” variables. Modeling of processes in this class differs from the conventional parametric models represented the surface in the same space. One should apply the appropriate non-parametric indicators while building learning parametric models of the “tubular” processes. Some specific examples of “tubular” processes modeling are considered. It follows from them that the processes are in spaces of fractional dimension. The case of the function with multiple variables is given and the situation when these variables can “disappear” and “occur again” is analyzed. It is shown that the calculation of fractional dimension space can be realized in different ways.

Keywords

АПРИОРНАЯ ИНФОРМАЦИЯ, ИДЕНТИФИКАЦИЯ, НЕПАРАМЕТРИЧЕСКАЯ МОДЕЛЬ, НЕПАРАМЕТРИЧЕСКИЕ АЛГОРИТМЫ, H-МОДЕЛИ, ПРОСТРАНСТВО ДРОБНОЙ РАЗМЕРНОСТИ

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average