A new 2-D fast RLS algorithm

Author

Sequeira, A.M. ; Therrien, C.W.

Author_Institution

US Naval Postgraduate Sch., Monterey, CA, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

1401

Abstract

A two-dimensional fast recursive least-squares algorithm is presented using a geometrical formulation based on the mathematical concepts of vector space, orthorgonal projection, and subspace decomposition. By appropriately ordering the 2-D data, the algorithm provides an exact least-squares solution to the deterministic normal equations. The method is further extended to the general FIR (finite impulse response) Wiener filter and the ARMA (autoregressive moving-average) modeling. The size and shape of the support region for both the MA and AR coefficients of the filter can be chosen arbitrarily

Keywords

adaptive filters; filtering and prediction theory; least squares approximations; two-dimensional digital filters; 2-D fast RLS algorithm; ARMA; FIR; adaptive filtering; autoregressive moving average modelling; deterministic normal equations; exact least-squares solution; finite impulse response Wiener filter; orthorgonal projection; subspace decomposition; two-dimensional fast recursive least-squares algorithm; vector space; Adaptive filters; Equations; Filtering algorithms; Finite impulse response filter; Least squares methods; Nonlinear filters; Resonance light scattering; Shape; Signal processing algorithms; Transversal filters; Vectors; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115651

Filename

115651