Dual-state systolic architectures for up/downdating RLS adaptive filtering

Author

Hsieh, S.F. ; Liu, K.J.R. ; Yao, K.

Author_Institution

Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan

Volume

39

Issue

6

fYear

1992

fDate

6/1/1992 12:00:00 AM

Firstpage

382

Lastpage

385

Abstract

A dual-state systolic structure to perform joint up/down-dating operations encountered in windowed recursive least-squares, (RLS) estimation problems is proposed. It is based on successively performing Givens rotations for updating and hyperbolic rotations for downdating. Due to data independence, a series of Givens and hyperbolic rotations can be interleaved and parallel processing can be achieved by alternatively performing updating and downdating both in time and space. This flip-flop nature of up/down-dating characterizes the feature of the dual-state systolic triarray. Efficient implementation on the evaluation of optimal residuals is also considered. This systolic architecture is promising for the VLSI implementation of fixed size sliding-window recursive least-squares estimations

Keywords

adaptive filters; digital filters; filtering and prediction theory; matrix algebra; systolic arrays; Givens rotations; RLS adaptive filtering; VLSI implementation; downdating; dual-state systolic structure; fixed size sliding-window; hyperbolic rotations; interleaving; joint up/down-dating operations; optimal residuals; parallel processing; recursive least-squares estimations; systolic architectures; systolic triarray; updating; windowed RLS estimation; Adaptive filters; Adaptive signal processing; Councils; Filtering; Parallel processing; Recursive estimation; Resonance light scattering; Signal processing algorithms; Systolic arrays; Very large scale integration;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.145296

Filename

145296