WEIGHTED ESTIMATION AND TRACKING FOR ARMAX MODELS

For complex multivariate ARMAX models, the author studies the weighted least squares algorithm which offers, by the choice of suitable weightings, the advantages of both the extended least squares and the stochastic gradient algorithms. Concerning adaptive tracking problems, the strong consistency of the estimator and control optimality are both ensured. Almost sure rates of convergence are also provided.