Choosing the Spectral Window in the Estimation of the Spectrum of a Gaussian Stationary Stochastic Process

Estimates of the spectral density of a discrete-time Gaussian stationary process are investigated. Weighting functions (spectral windows) are found for the estimates, permitting the mean-square error of estimation (or the upper bound thereof) to be minimized under specified assumptions regarding the degree of smoothness of the estimated density.