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

verfasst von

Jianbing Chen, Liam Comerford, Yongbo Peng, Michael Beer, Jie Li

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.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

Tongji University
The University of Liverpool

Typ

Artikel

Journal

Mechanical Systems and Signal Processing

Band

141

ISSN

0888-3270

Publikationsdatum

07.2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Steuerungs- und Systemtechnik, Signalverarbeitung, Tief- und Ingenieurbau, Luft- und Raumfahrttechnik, Maschinenbau, Angewandte Informatik

Elektronische Version(en)

https://doi.org/10.1016/j.ymssp.2020.106718 (Zugang: Geschlossen)