TFARMA models: order estimation and stabilization

The time-frequency ARMA (TFARMA) model is introduced as a time-varying ARMA model for nonstationary random processes that is formulated in terms of time shifts and frequency (Doppler) shifts. We present Akaike and minimum description length information criteria for the practically important task of selecting the TFARMA model orders. Because the estimated inverse filter used by the resulting order selection procedures is not guaranteed to be stable, we propose an iterative stabilization algorithm that is based on the concepts of instantaneous roots and root reflection/shrinkage. The performance of the proposed order selection and stabilization techniques is assessed through simulation.