New results on estimation bandwidth adaptation

Abstract The problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown and/or time-varying degree of signal nonstationary. The new rule is compared with the previously proposed one, based on the generalized Akaike’s final prediction error criterion.