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Electronics Letters
Article . 1991 . Peer-reviewed
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Easy and effective stabilisation measure for fast recursive least squares algorithms for adaptive transversal filters

Easy and effective stabilization measure for fast recursive least squares algorithms for adaptive transversal filters
descriptionPublicationkeyboard_double_arrow_right Article 01 Aug 1991 English Publisher:Institution of Engineering and Technology (IET)Journal:Electronics Letters, volume 27, pages 1,397-1,399 (issn: 0013-5194, eissn: 1350-911X, Copyright policy )
Authors: Schütze, H.; Ren, Z.;

doi: 10.1049/el:19910877

Easy and effective stabilisation measure for fast recursive least squares algorithms for adaptive transversal filters

Abstract

Summary: Fast recursive least squares (FRLS) algorithms are known for their favourable convergence characteristics. They are of special interest for the fast adaptation of transversal filters of high order \(N\). Unfortunately FRLS algorithms have a tendency towards numeric instability. A new and effective stabilization measure is presented for a \(0(7N)\) FRLS algorithm which needs only one additional multiplication per iteration step.

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Keywords

Least squares and related methods for stochastic control systems, fast recursive least squares algorithms, Filtering in stochastic control theory

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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!
4
Average
Top 10%
Average
gold