WIENER–KOLMOGOROV FILTERING, FREQUENCY-SELECTIVE FILTERING, AND POLYNOMIAL REGRESSION

Adaptations of the classical Wiener–Kolmogorov filters are described that enable them to be applied to short nonstationary sequences+ Alternative filtering methods that operate in the time domain and the frequency domain are described+ The frequency-domain methods have the advantage of allowing components of the data to be separated along sharp dividing lines in the frequency domain, without incurring any leakage+ The paper contains a novel treatment of the start-up problem that affects the filtering of trended data sequences+