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

descriptionPublicationkeyboard_double_arrow_right Article 24 Dec 2002Publisher:IEEEJournal:Proceedings of 35th IEEE Conference on Decision and Control, volume 1, pages 1,079-1,080
Authors: P. Carrette;

doi: 10.1109/cdc.1996.574645

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

Abstract

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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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
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