For a zero-mean stationary Gaussian random field , the unnormalized autocorrelation function of a random field isIt depends only on the separation , and is the pointwise variance. If , the normalized correlation is ; the two conventions have different units.
For a mean-square continuous field, its spectral measure of a stationary random field obeys . If is integrable, an ordinary power spectral density exists and, in the angular-wavevector convention,Thus has density . A spectral measure need not have a density: a spatially constant centered Gaussian field of variance has and spectral measure , concentrated at zero wavevector. Calling every spectrum an ordinary function would miss this case.[ref]
Gaussian Processes for Machine Learning by Carl Edward Rasmussen and Christopher K. I. Williams. Chapter 4, Section 4.1, Bochner representation and spectral-density distinction; Fourier factors explicitly chosen here
For , the covariance function is . It involves fourth moments and is not determined by the two-point correlation of in general. For a centered Gaussian pair the fourth-moment identity reduces it to . This extra Gaussian hypothesis must be stated before using that reduction.
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