Schmucker-Weidelt Lecture Notes, Aarhus, 1975 - MTNet
Schmucker-Weidelt Lecture Notes, Aarhus, 1975 - MTNet
Schmucker-Weidelt Lecture Notes, Aarhus, 1975 - MTNet
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- - .<br />
the same or from different sites. Let Z(w>, X(w), Y(w) be the Fouri-er<br />
transforms of Z(t), XCt) and Y(t). Then a linear relation of the<br />
form<br />
- -<br />
is established in which A and B represent the desired transfer func- -<br />
tions between Z on the one side and X and Y on the other side; 6Z is<br />
the uncorrelated "noise" in 2, assuming X and Y to be noise-free.<br />
As the best fitting transfer - functions will be considered those whicf<br />
produce minLmum noise < 16zI2 > in the statistical average. Here the<br />
average is to be taken either over a number of records -- or within<br />
extended frequency bands of the width which is L times greater<br />
than the ultimate spacing IL'T of individual spectral estimates. The<br />
noise: signal ratio defines the residual e(w) ,%atio of related to<br />
observed signal the . --- coherence R(w):<br />
The coherence in conjunction with the degree of freedom of the<br />
- -<br />
functions A and B.<br />
averaging procedure estab1ishe.s confidence limits for -the transfer<br />
The averaged products of Fourier transforms are denoted as<br />
S<br />
ZZ<br />
., -<br />
= < Z Z * >: power spectrum of Z.<br />
- -<br />
S = < Z Y * >: cross spectrum between Z and Y<br />
ZY<br />
wi-th S = S* .<br />
ZY Y =<br />
In summary, the data reduction involves the following steps<br />
(a) Fourier transformation of tiine records<br />
(b) Calculations of power and cross-spectra<br />
(c) Calculation of transfer functions<br />
(d) )COlculation of confidence limits for the trans-<br />
ferfunctions.<br />
Steps Ca) and (bf can be substi.cuted by the foll.owing alternatives:<br />
(ax) : Calculate auto-correlation functions ) , .. . and cross-<br />
correlation f.urictf.ons R , . . . with T being a time lag,<br />
ZY<br />