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.