Title :
Tuning the forgetting factor in RLS identification algorithms
Author :
Bittanti, Sergio ; Camp, Marco
Author_Institution :
Dipartimento di Elettronica, Politecnico di Milano, Italy
Abstract :
An upper bound for the parameter tracking error of RLS (recursive least squares) identification algorithms with forgetting factor (FF) is worked out in a fully stochastic framework. By minimizing such a bound, the selection of a suitable value for the FF can be performed
Keywords :
identification; optimisation; self-adjusting systems; statistical analysis; stochastic processes; forgetting factor tuning; parameter tracking error; recursive least squares identification; stochastic processes; upper bound; Equations; Guidelines; Least squares approximation; Least squares methods; Parameter estimation; Recursive estimation; Resonance light scattering; State estimation; Stochastic processes; Stochastic systems; Upper bound;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261695
