The fast adaptive ROTOR´s RLS algorithm

Author

Cioffi, J.M.

Author_Institution

Dept. of Electr. Eng., Stanford Univ., CA

Volume

38

Issue

4

fYear

1990

fDate

4/1/1990 12:00:00 AM

Firstpage

631

Lastpage

653

Abstract

A fast algorithm for implementation of the QR-factorization-based recursive-least-squares (RLS) adaptive filter is discussed. This fast adaptive rotors (FAR) algorithm can be implemented with a pipelined array of processors called ROTORs and CISORs. The ROTORs compute 2×2 orthogonal (Givens) rotations, and the CISORs compute the cosines and sines of the angles used in the ROTORs. The algorithm requires 4N ROTORs and 2N CISORs at each iteration to compute the solution to the RLS problem. The algorithm is numerically stable. The FAR algorithm is derived using a single generic updating formula for orthogonal matrices, which is introduced and derived. Whereas the generic updating formula is reminiscent of previous fast transversal filters and fast lattice algorithms, the set of internally propogated adaptive filter quantities is entirely different and constitutes yet another complete characterization of the RLS covariance and the forward, backward, and pinning estimation problems

Keywords

adaptive filters; computerised signal processing; least squares approximations; pipeline processing; CISOR; QR factorisation; RLS adaptive filter; RLS covariance; ROTOR; backward estimation; cosines; fast adaptive rotors algorithm; forward estimation; orthogonal matrices; pinning estimation; pipelined array; pipelined processors; sines; Adaptive arrays; Adaptive filters; Covariance matrix; Forward contracts; Lattices; Least squares methods; Modems; Resonance light scattering; Signal processing algorithms; Transversal filters;

fLanguage

English

Journal_Title

Acoustics, Speech and Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

0096-3518

Type

jour

DOI

10.1109/29.52704

Filename

52704