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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 />

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