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A hybrid lattice-QR fast algorithm for least squares adaptive filtering

Authors: P.A. Regalia; M.G. Bellanger;

A hybrid lattice-QR fast algorithm for least squares adaptive filtering

Abstract

The fact that lattice and QR methods of adaptive least-squares filtering follow from the same geometric framework allows the first solution to the parameter identification problem using fast QR techniques. These relations suggest combining QR and lattice algorithms into hybrid algorithms of low complexity and good numerical behavior. It is emphasized that many other possibilities are available for mixing and matching the steps of QR and lattice algorithms. The various algorithms so obtained differ in their computational complexity, accessibility to desired variables, etc., but all work within a related geometric framework. >

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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
Average
Average
Average
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