Accurate estimation of evolutionary power spectra for strongly narrow-band random fields

Schillinger, D; Papadopoulos, V

dc.contributor.author	Schillinger, D	en
dc.contributor.author	Papadopoulos, V	en
dc.date.accessioned	2014-03-01T01:32:36Z
dc.date.available	2014-03-01T01:32:36Z
dc.date.issued	2010	en
dc.identifier.issn	0045-7825	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20187
dc.subject	Evolutionary power spectrum estimation	en
dc.subject	Method of separation	en
dc.subject	Narrow-band random fields	en
dc.subject	Space-frequency localization	en
dc.subject	Spectral representation	en
dc.subject.classification	Engineering, Multidisciplinary	en
dc.subject.classification	Mathematics, Interdisciplinary Applications	en
dc.subject.classification	Mechanics	en
dc.subject.other	Evolutionary power spectrum	en
dc.subject.other	Method of separation	en
dc.subject.other	Narrow bands	en
dc.subject.other	Space-frequency localization	en
dc.subject.other	Spectral representations	en
dc.subject.other	Estimation	en
dc.subject.other	Power spectrum	en
dc.subject.other	Spectrum analysis	en
dc.subject.other	Wavelet transforms	en
dc.subject.other	Frequency estimation	en
dc.title	Accurate estimation of evolutionary power spectra for strongly narrow-band random fields	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cma.2009.11.008	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cma.2009.11.008	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	One of the most widely used techniques for the simulation of non-homogeneous random fields is the spectral representation method. Its key quantity is the power spectrum, which characterizes the random field in terms of frequency content and spatial evolution in a mean square sense. The paper at hand proposes a method for the estimation of separable power spectra from a series of samples, which combines accurate spectrum resolution in space with an optimum localization in frequency. For non-separable power spectra, it can be complemented by a joint strategy, which is based on the partitioning of the space-frequency domain into several sub-spectra that have to be separable only within themselves. Characteristics and accuracy of the proposed method are demonstrated for analytical benchmark spectra, whose estimates are compared to corresponding results of established techniques based on the short-time Fourier, the harmonic wavelet and the Wigner-Ville transforms. It is then shown by a practical example from stochastic imperfection modeling in structures that in the presence of strong narrow-bandedness in frequency, the proposed method for separable random fields leads to a considerable improvement of estimation results in comparison to the established techniques. (c) 2009 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE SA	en
heal.journalName	Computer Methods in Applied Mechanics and Engineering	en
dc.identifier.doi	10.1016/j.cma.2009.11.008	en
dc.identifier.isi	ISI:000276629400001	en
dc.identifier.volume	199	en
dc.identifier.issue	17-20	en
dc.identifier.spage	947	en
dc.identifier.epage	960	en