Details
| Original language | English |
|---|---|
| Article number | 106718 |
| Journal | Mechanical Systems and Signal Processing |
| Volume | 141 |
| Early online date | 19 Feb 2020 |
| Publication status | Published - Jul 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.
Keywords
- Power spectrum, Random frequencies, Stochastic Harmonic Function, Stochastic process, System response spectrum
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Computer Science(all)
- Signal Processing
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Aerospace Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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In: Mechanical Systems and Signal Processing, Vol. 141, 106718, 07.2020.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Reduction of random variables in the Stochastic Harmonic Function representation via spectrum-relative dependent random frequencies
AU - Chen, Jianbing
AU - Comerford, Liam
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.
PY - 2020/7
Y1 - 2020/7
N2 - 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.
AB - 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.
KW - Power spectrum
KW - Random frequencies
KW - Stochastic Harmonic Function
KW - Stochastic process
KW - System response spectrum
UR - http://www.scopus.com/inward/record.url?scp=85079523082&partnerID=8YFLogxK
U2 - 10.1016/j.ymssp.2020.106718
DO - 10.1016/j.ymssp.2020.106718
M3 - Article
AN - SCOPUS:85079523082
VL - 141
JO - Mechanical Systems and Signal Processing
JF - Mechanical Systems and Signal Processing
SN - 0888-3270
M1 - 106718
ER -