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Data-based mechanistic modelling of engineering systems.

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Data-based mechanistic modelling of engineering systems. / Young, Peter C.
In: Journal of Vibration and Control, Vol. 4, No. 1, 01.1998, p. 5-28.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Young PC. Data-based mechanistic modelling of engineering systems. Journal of Vibration and Control. 1998 Jan;4(1):5-28. doi: 10.1177/107754639800400102

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Young, Peter C. / Data-based mechanistic modelling of engineering systems. In: Journal of Vibration and Control. 1998 ; Vol. 4, No. 1. pp. 5-28.

Bibtex

@article{83ee741ed8a4453481dc77a54f573a6d,
title = "Data-based mechanistic modelling of engineering systems.",
abstract = "This paper outlines a new approach to the statistical identification and estimation of dynamic models for a widely applicable class of linear and nonlinear systems based on a combination of nonparametric and parametric estimation procedures. The new approach is applied to three systems: a chaotic version of the discrete-time logistic growth equation; a continuous-time, second-order nonlinear system with two feedback nonlinearities; and a predominantly linear but high-order, vibrating cantilever beam.",
keywords = "Identification • estimation • linear and nonlinear systems • state dependent parameters • vibrating beam",
author = "Young, {Peter C.}",
year = "1998",
month = jan,
doi = "10.1177/107754639800400102",
language = "English",
volume = "4",
pages = "5--28",
journal = "Journal of Vibration and Control",
issn = "1741-2986",
publisher = "SAGE Publications Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Data-based mechanistic modelling of engineering systems.

AU - Young, Peter C.

PY - 1998/1

Y1 - 1998/1

N2 - This paper outlines a new approach to the statistical identification and estimation of dynamic models for a widely applicable class of linear and nonlinear systems based on a combination of nonparametric and parametric estimation procedures. The new approach is applied to three systems: a chaotic version of the discrete-time logistic growth equation; a continuous-time, second-order nonlinear system with two feedback nonlinearities; and a predominantly linear but high-order, vibrating cantilever beam.

AB - This paper outlines a new approach to the statistical identification and estimation of dynamic models for a widely applicable class of linear and nonlinear systems based on a combination of nonparametric and parametric estimation procedures. The new approach is applied to three systems: a chaotic version of the discrete-time logistic growth equation; a continuous-time, second-order nonlinear system with two feedback nonlinearities; and a predominantly linear but high-order, vibrating cantilever beam.

KW - Identification • estimation • linear and nonlinear systems • state dependent parameters • vibrating beam

U2 - 10.1177/107754639800400102

DO - 10.1177/107754639800400102

M3 - Journal article

VL - 4

SP - 5

EP - 28

JO - Journal of Vibration and Control

JF - Journal of Vibration and Control

SN - 1741-2986

IS - 1

ER -