Cross-spectrum

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Template:Technical In time series analysis, the cross-spectrum is used as part of a frequency domain analysis of the cross-correlation or cross-covariance between two time series.

Definition

Let (Xt,Yt) represent a pair of stochastic processes that are jointly wide sense stationary with autocovariance functions γxx and γyy and cross-covariance function γxy. Then the cross-spectrum Γxy is defined as the Fourier transform of γxy [1]

Γxy(f)={γxy}(f)=τ=γxy(τ)e2πiτf,

where

γxy(τ)=E[(xtμx)(yt+τμy)] .

The cross-spectrum has representations as a decomposition into (i) its real part (co-spectrum) and (ii) its imaginary part (quadrature spectrum)

Γxy(f)=Λxy(f)iΨxy(f),

and (ii) in polar coordinates

Γxy(f)=Axy(f)eiϕxy(f).

Here, the amplitude spectrum Axy is given by

Axy(f)=(Λxy(f)2+Ψxy(f)2)12,

and the phase spectrum Φxy is given by

{tan1(Ψxy(f)/Λxy(f))if Ψxy(f)0 and Λxy(f)00if Ψxy(f)=0 and Λxy(f)>0±πif Ψxy(f)=0 and Λxy(f)<0π/2if Ψxy(f)>0 and Λxy(f)=0π/2if Ψxy(f)<0 and Λxy(f)=0

Squared coherency spectrum

The squared coherency spectrum is given by

κxy(f)=Axy2Γxx(f)Γyy(f),

which expresses the amplitude spectrum in dimensionless units.

See also

References