Title :
Least squares identification of autoregressive models with time-varying parameters
Author :
Bittanti, Sergio ; Campi, Marco
Author_Institution :
Dipartimento di Elettronica e Inf., Politecnico di Milano, Italy
Abstract :
The estimate of the parameters of time-varying autoregressive models is often performed with the recursive least squares algorithm equipped with exponential forgetting. In this paper, we study the properties of these estimates when the parameter variation is governed by a stable equation subject to an L2-bounded drift. Under suitable assumptions, we show that if the forgetting factor is large enough then the tracking error keeps bounded, and has an interesting expression
Keywords :
autoregressive processes; least squares approximations; recursive estimation; time-varying systems; L2-bounded drift; autoregressive models; exponential forgetting; least-squares identification; recursive least-squares algorithm; stable equation; time-varying parameter estimation; Cost function; Delay; Equations; Lakes; Least squares approximation; Least squares methods; Parameter estimation; Recursive estimation; Resonance light scattering; Stochastic processes;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411711
