Recursive identification of noisy autoregressive models via a noise-compensated overdetermined instrumental variable method - Barbieri, Matteo; Diversi, Roberto (Zielona Góra: Uniwersytet Zielonogórski)
The aim of this paper is to develop a new recursive identification algorithm for autoregressive (AR) models corrupted by additive white noise. The proposed approach relies on a set of both low-order and high-order Yule-Walker equations and on a modified version of the overdetermined recursive instrumental variable method, leading to the estimation of both the AR coefficients and the additive noise variance.
Keywords: system identification; noisy autoregressive models; recursive estimation; Yule-Walker equations; condition monitoring systems