Nonlinear dynamic system kernel based reconstruction from time series data

dc.contributor.author	Lyubchyk, Leonid	en
dc.contributor.author	Kolbasin, Vladislav	en
dc.contributor.author	Grinberg, Galina	en
dc.date.accessioned	2018-06-21T09:39:35Z
dc.date.available	2018-06-21T09:39:35Z
dc.date.issued	2015
dc.description.abstract	A unified approach to reccurent kernel identification algorithms design is proposed. In order to fix the auxiliary vector dimension, the reduced order model kernel method is proposed and proper reccurent identification algorithms are designed.	en
dc.identifier.citation	Lyubchyk L. M. Nonlinear dynamic system kernel based reconstruction from time series data / L. M. Lyubchyk, V. A. Kolbasin, G. L. Grinberg // Problems of Decision Making under Uncertainties (PDMU–2015) : XXV International Conference, may 11-16 2015, pp. 34-35.	en
dc.identifier.orcid	https://orcid.org/0000-0002-0774-5414
dc.identifier.uri	https://repository.kpi.kharkov.ua/handle/KhPI-Press/36826
dc.language.iso	en
dc.publisher	ТВіМС	en
dc.subject	time-series data	en
dc.subject	kernel method	en
dc.subject	identification algorithm	en
dc.subject	intelligent data analysis	en
dc.title	Nonlinear dynamic system kernel based reconstruction from time series data	en
dc.type	Thesis	en

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