Stochastic Spectral and Fourier-Wavelet Methods for Vector Gaussian Random Fields
Kurbanmuradov O. and
Sabelfeld K.
Additional contact information
Kurbanmuradov O.: 1. Center for Phys. Math. Research, Turkmenian State University, Turkmenbashy av. 31, 744000 Ashgabad, Turkmenistan
Sabelfeld K.: 2. Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstrasse 39, D – 10117 Berlin, Germany sabelfel@wias-berlin.de
Monte Carlo Methods and Applications, 2006, vol. 12, issue 5, 395-445
Abstract:
Randomized Spectral Models (RSM) and Randomized Fourier-Wavelet Models (FWM) for simulation of homogeneous Gaussian random fields based on spectral representations and plane wave decomposition of random fields are developed. Extensions of FWM to vector random processes are constructed. Convergence of the constructed Fourier-Wavelet models (in the sense of finite-dimensional distributions) under some general conditions on the spectral tensor is given. A comparative analysis of RSM and FWM is made by calculating Eulerian statistical characteristics of a 3D isotropic incompressible random field through an ensemble and space averaging.
Date: 2006
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://doi.org/10.1515/156939606779329080 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:mcmeap:v:12:y:2006:i:5:p:395-445:n:8
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/mcma/html
DOI: 10.1515/156939606779329080
Access Statistics for this article
Monte Carlo Methods and Applications is currently edited by Karl K. Sabelfeld
More articles in Monte Carlo Methods and Applications from De Gruyter
Bibliographic data for series maintained by Peter Golla (peter.golla@degruyter.com).