Please use this identifier to cite or link to this item: https://oar.tib.eu/jspui/handle/123456789/1886
Files in This Item:
File SizeFormat 
546266711.pdf245.88 kBAdobe PDFView/Open
Title: Convergence of Fourier-Wavelet models for Gaussian random processes
Authors: Kurbanmuradov, OrazgeldiSabelfeld, Karl
Issue Date: 2007
Published in: Preprint / Weierstraß-Institut für Angewandte Analysis und Stochastik , Volume 1239, ISSN 0946-8633
Publisher: Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
Abstract: Mean square convergence and convergence in probability of Fourier-Wavelet Models (FWM) of stationary Gaussian Random processes in the metric of Banach space of continuously differentiable functions and in Sobolev space are studied. Sufficient conditions for the convergence formulated in the frame of spectral functions are given. It is shown that the given rates of convergence of FWM in the mean square obtained in the Nikolskiui-Besov classes cannot be improved.
Keywords: Fourier-Wavelet model; stationary Gaussian random process; Meyer’s wavelets; Nikolski˘i-Besov space; convergence in probability; convergence in mean square
DDC: 510
License: This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.
Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Appears in Collections:Mathematik



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.