Correction to "Multiresolution Representations Using the Autocorrelation Functions of Compactly Supported Wavelets"
Naoki Saito, Gregory Beylkin, P. Taneli Harju · 1997
We derive an FIR polynomial predictor for data in which some samples are missing. The method is compared with a computation- ally lighter algorithm that is based on decision-driven recursion. Both schemes are found to perform almost identically well on predicting a sinusoidal signal corrupted by both impulsive and Gaussian noise.