Adaptive general parameter extension for tuning FIR predictors

Abstract

A general parameter (GP) extension to expand the applicability of discrete time finite impulse response (FIR) filters designed for sinusoidal or polynomial signal prediction while attenuating white noise is proposed. These FIR filters are simple and powerful linear methods for filtering, predicting and modeling many real world phenomena. With only a single adaptive GP, it is computationally efficiently possible to extend prediction capabilities of polynomial and sinusoidal FIR predictors beyond their design input signal models, i.e., beyond polynomial input signals, or nominal design frequencies, respectively. This allows for more accurate prediction of signals with time varying characteristics.