Analysis of a constrained forgetting factor recursive least squares algorithm in system identification

In this paper, we deal with deterministic dominance of stochastic equations. The obtained results lead to the evaluation of tight upper-bounds upon the parameter tracking error of the forgetting factor recursive least squares (RLS) algorithm applied to the identification of time-varying systems.

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Bibliographic Details
Published in:Proceedings of 35th IEEE Conference on Decision and Control Vol. 1; pp. 1079 - 1080 vol.1
Main Author: Carrette, P.
Format: Conference Proceeding
Language:English
Published: IEEE 1996
Subjects:
Algorithm design and analysis
Equations
Least squares approximation
Least squares methods
Parameter estimation
Recursive estimation
Resonance light scattering
Stochastic processes
System identification
Time varying systems
ISBN:9780780335905, 0780335902
ISSN:0191-2216
Online Access:Get full text
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Description
Summary:In this paper, we deal with deterministic dominance of stochastic equations. The obtained results lead to the evaluation of tight upper-bounds upon the parameter tracking error of the forgetting factor recursive least squares (RLS) algorithm applied to the identification of time-varying systems.
ISBN:9780780335905
0780335902
ISSN:0191-2216
DOI:10.1109/CDC.1996.574645