Bivariate Processes Evolutionary Power Spectral Density Estimation Using Energy Spectrum Equations

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dc.citation.articleNumber252009en_US
dc.citation.issueNumber25en_US
dc.citation.journalTitleJournal of Physics: Conference Seriesen_US
dc.citation.volumeNumber2647en_US
dc.contributor.authorSpanos, Pol D.en_US
dc.contributor.authorMatteo, Alberto Dien_US
dc.contributor.authorZhang, Hanshuen_US
dc.contributor.authorYue, Qingxiaen_US
dc.date.accessioned2024-08-02T13:32:08Zen_US
dc.date.available2024-08-02T13:32:08Zen_US
dc.date.issued2024en_US
dc.description.abstractIn this paper a novel procedure is developed for evolutionary cross power spectra (ECPS) estimation of bivariate nonstationary stochastic processes. Specifically, the ECPS is determined by estimating the statistical moments of energy-like response quantities of lightly damped linear filters excited by nonstationary stochastic processes. In this context, a smoothing procedure is incorporated by using the Savitzky-Golay (S-G) moving average filter to obtain reliable ECPS based even from a limited number of available records. Further, a refinement of the approach is proposed relying on polynomial based functions of the system output. Several numerical examples, including nonstationary processes with known spectra, and historic accelerograms are used to assess the reliability and accuracy of the proposed procedure.en_US
dc.identifier.citationSpanos, P. D., Matteo, A. D., Zhang, H., & Yue, Q. (2024). Bivariate Processes Evolutionary Power Spectral Density Estimation Using Energy Spectrum Equations. Journal of Physics: Conference Series, 2647(25), 252009. https://doi.org/10.1088/1742-6596/2647/25/252009en_US
dc.identifier.digitalSpanos_2024_J_Phys__Conf_Ser_2647_252009en_US
dc.identifier.doihttps://doi.org/10.1088/1742-6596/2647/25/252009en_US
dc.identifier.urihttps://hdl.handle.net/1911/117565en_US
dc.language.isoengen_US
dc.publisherIOP Publishingen_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license.  Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleBivariate Processes Evolutionary Power Spectral Density Estimation Using Energy Spectrum Equationsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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