A Recursive Least Squares Algorithm for Pseudo-Linear ARMA Systems Using the Auxiliary Model and the Filtering Technique

摘要

In this paper, we study the parameter estimation problem for pseudo-linear autoregressive moving average systems. The key is to use the data filtering technique to obtain a pseudo-linear identification model and to derive an auxiliary model-based recursive least squares algorithm through filtering the observation data. The simulation results confirm the effectiveness of the proposed algorithm.