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An enhanced model parameter estimation by a slow-fast decomposition based on the first order two time-scale expansion
- 1.0566422 - ÚTIA 2023 CZ eng A - Abstract
Papáček, Štěpán - Matonoha, Ctirad
An enhanced model parameter estimation by a slow-fast decomposition based on the first order two time-scale expansion.
Proceedings of the PANM 21 Programy a algoritmy numericke matematiky 21 /2022/. Praha: Institute of Mathematics Czech Academy of Sciences, 2023. s. 19-19.
[PANM 21 Programy a algoritmy numericke matematiky 21 /2022/. 19.06.2022-24.06.2022, Jablonec nad Nisou]
R&D Projects: GA ČR(CZ) GA21-03689S
Institutional support: RVO:67985556 ; RVO:67985807
Keywords : Dynamical systems * Estimated parameters
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2023/TR/papacek-0566422.pdf
Some dynamical systems, e.g. biochemical networks, are characterized by more than one time scale. On the paradigmatic example of a drug-induced enzyme production we show how the slow-fast decomposition can serve for an enhanced parameter estimation when the slowly changing features are rigorously incorporated.
Permanent Link: https://hdl.handle.net/11104/0337777
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