Estimation Problems for Periodically Correlated Isotropic Random FieldsEstimation Problems for Random Fields

被引:0
作者
Iryna Dubovetska
Oleksandr Masyutka
Mikhail Moklyachuk
机构
[1] Kyiv National Taras Shevchenko University,Department of Probability Theory, Statistics and Actuarial Mathematics
[2] Kyiv National Taras Shevchenko University,Department of Mathematics and Theoretical Radiophysics
来源
Methodology and Computing in Applied Probability | 2015年 / 17卷
关键词
Random field; Prediction; Filtering; Robust estimate; Mean square error; Least favourable spectral densities; Minimax spectral characteristic; 60G60; 62M40; 62M20; 93E10; 93E11;
D O I
暂无
中图分类号
学科分类号
摘要
Spectral theory of isotropic random fields in Euclidean space developed by M. I. Yadrenko is exploited to find a solution to the problem of optimal linear estimation of the functional \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ A\zeta ={\sum\limits_{t=0}^{\infty}}\,\,\,{\int_{S_n}} \,\,a(t,x)\zeta (t,x)\,m_n(dx) $$\end{document}which depends on unknown values of a periodically correlated (cyclostationary with period T) with respect to time isotropic on the sphere Sn in Euclidean space En random field ζ(t, x), t ∈ Z, x ∈ Sn. Estimates are based on observations of the field ζ(t, x) + θ(t, x) at points (t, x), t = − 1, − 2, ..., x ∈ Sn, where θ(t, x) is an uncorrelated with ζ(t, x) periodically correlated with respect to time isotropic on the sphere Sn random field. Formulas for computing the value of the mean-square error and the spectral characteristic of the optimal linear estimate of the functional Aζ are obtained. The least favourable spectral densities and the minimax (robust) spectral characteristics of the optimal estimates of the functional Aζ are determined for some special classes of spectral densities.
引用
收藏
页码:41 / 57
页数:16
相关论文
共 35 条
[1]  
Adshead P(2012)Fast computation of first-order feature-bispectrum corrections Phys Rev D 85 103531-1036
[2]  
Hu W(2009)Cyclostationarity by examples Mech Syst Signal Process 23 987-109
[3]  
Antoni J(1999)The standard cosmological model and cmb anisotropies New Astron Rev 43 83-364
[4]  
Bartlett JG(1985)Minimax robust prediction of discrete time series Z Wahrscheinlichkeitstheor Verw Geb 68 337-388
[5]  
Franke J(1961)Periodically correlated random sequences Sov Math Dokl 2 385-379
[6]  
Gladyshev EG(1957)A prediction problem in game theory Ark Mat 3 371-216
[7]  
Grenander U(2002)Cosmic microwave background anisotropies Ann Rev Astron Astrophys 40 171-1802
[8]  
Hu W(1994)Hemispheric surface air temperature variations: a reanalysis and an update to 1993 J Climate 7 1794-181
[9]  
Dodelson S(1974)A view of three decades of linear filtering theory IEEE Trans Inf Theory 20 146-353
[10]  
Jones PD(2012)The bispectrum as a source of phase-sensitive invariants for Fourier descriptors: a group-theoretic approach J Math Imaging Vis 44 341-481