Properties of separable covariance matrices and their associated gaussian random processes.

ABSTRACT

A number of properties of separable covariance matrices are summarized. Expressions for the divergence of the corresponding two-dimensional Gaussian random processes are given in terms of row and column covariance matrices, and in terms of linear prediction parameters and maximum likelihood spectral estimates. Such time and frequency domain expressions are not widely known, even for one-dimensional random processes.