High speed RLS using scaled tangent rotations (STAR)

K. J. Raghunath, Keshab K Parhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

The QR decomposition based recursive least-squares (RLS) adaptive filtering algorithm (referred to as QRD-RLS) has a processing speed limitation. Fine-grain pipelining of the recursive loops within the cells using look-ahead techniques requires large hardward increase. In this paper, a new scaled tangent rotation (STAR) is used instead of the usual Givens rotations. The scaled tangent rotation (STAR) RLS algorithm (referred to as STAR-RLS) is designed such that fine-grain pipelining can be accomplished very easily. The scaled tangent rotations are not exactly orthogonal transformations but tend to become orthogonal asymptotically. Simulation results show that the algorithm performance is similar to that of the QRD-RLS algorithm. The STAR-RLS algorithm can be mapped onto a systolic array. The computational complexity and inter cell communications are considerably lower than the QRD-RLS algorithm and the square-root free techniques. An interesting aspect of the STAR-RLS systolic array is that the a priori estimation error can be obtained directly as the output of the last internal cell, without any extra computation.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherPubl by IEEE
Pages1959-1962
Number of pages4
ISBN (Print)0780312813
StatePublished - Jan 1 1993
EventProceedings of the 1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, USA
Duration: May 3 1993May 6 1993

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume3
ISSN (Print)0271-4310

Other

OtherProceedings of the 1993 IEEE International Symposium on Circuits and Systems
CityChicago, IL, USA
Period5/3/935/6/93

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