Open AccessSpectral Analysis for Geophysical Data
Author(s) -
Hannan E. J.
Publication year - 1966
Publication title -
geophysical journal of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0016-8009
DOI - 10.1111/j.1365-246x.1966.tb03502.x
Subject(s) - aliasing , homogeneous , sampling (signal processing) , fourier transform , spectral density , fourier analysis , spectral analysis , filter (signal processing) , noise (video) , function (biology) , series (stratigraphy) , mathematics , algorithm , mathematical analysis , statistical physics , computer science , physics , statistics , geology , paleontology , quantum mechanics , artificial intelligence , evolutionary biology , spectroscopy , image (mathematics) , computer vision , biology
Summary The Fourier methods which underlie the statistical analysis of four types of data are presented. These are (a) stationary time series, (b) homogeneous planar processes, (c) homogeneous processes on a sphere and (d) a combination of (a) with (b) or (c). The data to be analysed will be modified by the effects, (i) of filtering of the continuous phenomenon (e.g. by the recording device), (ii) discrete sampling of the continuous phenomenon, (iii) further filtering of the discrete record. The effects of these are analysed and described, in the case of (i) and (iii) by a description of the response function of the filter and in case (ii) by describing the‘aliasing’involved (i.e. degree of indistinguishability of spectral components). Procedures for estimating the spectrum of the discrete record are described. Signal measurement in noise problems (and to some extent their analogues in cases (b), (c), (d)) are discussed as a principal example of the final use of these spectral methods.