Designing method for ARMA four‐line lattice filter with sliding rectangular window

Abstract

AbstractThis paper derives a design method for an ARMA 4‐line lattice filter using a sliding rectangular window. The adaptive ARMA 4‐line lattice filter already proposed uses a forgetting factor, which is one of the weighting functions to estimate coefficients of a time‐varying system in which system coefficients vary with sufficient smoothness. Therefore, the effect of past observed signal over the estimated coefficients decreases exponentially.The filter presented here is realized using a rectangular window because the concern is over the effects of past observation signal rather than window length. Using this filter, an input signal is estimated when designing; furthermore, a system can be identified in which an arbitrary section in the frequency domain is weighted.Thus, by not only analyzing voice signal which is considered a model whose input signal is unknown and EEG data but also by weighting the frequency domain, for example, the holmant in the low‐frequency domain can be estimated in low degree with very high precision and a specific wave (such as a α activities) in EEG data can also be detected. Moreover, in this paper the algorithm is verified by model experiments.