New fast inverse QR least squares adaptive algorithms

Author

Rontogiannis, A.A. ; Theodoridis, S.

Author_Institution

Dept. of Inf., Athens Univ., Greece

Volume

2

fYear

1995

fDate

9-12 May 1995

Firstpage

1412

Abstract

The paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obtained via a QR decomposition (QRD). Both are of O(p) computational complexity with p being the order of the system. The first algorithm is a fixed order QRD scheme with enhanced parallelism. The second is a lattice type algorithm based on Givens rotations, with lower complexity compared to previously derived ones

Keywords

adaptive filters; computational complexity; correlation methods; digital filters; identification; inverse problems; lattice filters; least squares approximations; matrix decomposition; parallel algorithms; Givens rotations; LS system identification; QR decomposition; computational complexity; data correlation matrix; fast inverse QR least squares adaptive algorithms; inverse Cholesky factor; lattice type algorithm; parallelism; quadratic residue; Adaptive algorithm; Finite impulse response filter; Informatics; Lattices; Least squares methods; Parallel processing; Resonance light scattering; Robustness; Signal processing algorithms; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.480506

Filename

480506