Reduction of random variables in the Stochastic Harmonic Function representation via spectrum-relative dependent random frequencies

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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  • Tongji University
  • The University of Liverpool
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OriginalspracheEnglisch
Aufsatznummer106718
FachzeitschriftMechanical Systems and Signal Processing
Jahrgang141
Frühes Online-Datum19 Feb. 2020
PublikationsstatusVeröffentlicht - Juli 2020

Abstract

Two significant developments pertaining to the application of the Stochastic Harmonic Function representation of stochastic processes are presented. Together, they allow for Gaussian records to be simulated within the bounds of the representation with the fewest number of random variables. Specifically, independent random frequencies that form a staple component of the Stochastic Harmonic Function are replaced by dependent random frequencies, along with a specific scheme for choosing frequency interval widths. Numerical examples demonstrating spectrum reconstruction accuracy and estimated PDF convergence to the Gaussian are presented to support the work.

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Reduction of random variables in the Stochastic Harmonic Function representation via spectrum-relative dependent random frequencies. / Chen, Jianbing; Comerford, Liam; Peng, Yongbo et al.
in: Mechanical Systems and Signal Processing, Jahrgang 141, 106718, 07.2020.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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abstract = "Two significant developments pertaining to the application of the Stochastic Harmonic Function representation of stochastic processes are presented. Together, they allow for Gaussian records to be simulated within the bounds of the representation with the fewest number of random variables. Specifically, independent random frequencies that form a staple component of the Stochastic Harmonic Function are replaced by dependent random frequencies, along with a specific scheme for choosing frequency interval widths. Numerical examples demonstrating spectrum reconstruction accuracy and estimated PDF convergence to the Gaussian are presented to support the work.",
keywords = "Power spectrum, Random frequencies, Stochastic Harmonic Function, Stochastic process, System response spectrum",
author = "Jianbing Chen and Liam Comerford and Yongbo Peng and Michael Beer and Jie Li",
note = "Funding information: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) and National Natural Science Foundation of China (NSFC) under the Sino-German research project: BE 2570/4-1, CO 1849/1-1 (DFG) 11761131014 (NSFC). The work was additionally supported by NSFC projects: 51725804, 11672209 & 51678450.",
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AU - Peng, Yongbo

AU - Beer, Michael

AU - Li, Jie

N1 - Funding information: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) and National Natural Science Foundation of China (NSFC) under the Sino-German research project: BE 2570/4-1, CO 1849/1-1 (DFG) 11761131014 (NSFC). The work was additionally supported by NSFC projects: 51725804, 11672209 & 51678450.

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