Fast orthogonal iteration adaptive algorithms for the generalized symmetric eigenproblem

Author

Strobach, Peter

Author_Institution

Fachhochschule Furtwangen, Germany

Volume

46

Issue

12

fYear

1998

fDate

12/1/1998 12:00:00 AM

Firstpage

3345

Lastpage

3359

Abstract

A class of sequential orthogonal iteration updating algorithms for the time-varying generalized symmetric eigenproblem (GSE) is presented. These algorithms are maximally fast, requiring N²+O(Nr) arithmetic operations each time step for tracking the r dominant eigenvectors and eigenvalues of an exponentially updated GSE of dimension N. Applications to subspace adaptive filtering and frequency estimation are also discussed. Detailed computer experiments lend empirical support to the theoretical findings

Keywords

adaptive filters; adaptive signal processing; eigenvalues and eigenfunctions; filtering theory; frequency estimation; iterative methods; adaptive signal processing; arithmetic operations; computer experiments; eigenvalues; eigenvectors; exponentially updated GSE; fast orthogonal iteration adaptive algorithms; frequency estimation; maximally fast algorithms; sequential orthogonal iteration updating algorithms; subspace adaptive filtering; time-varying generalized symmetric eigenproblem; Adaptive algorithm; Adaptive filters; Arithmetic; Covariance matrix; Eigenvalues and eigenfunctions; Filtering algorithms; Gaussian processes; Interference; Signal processing; Signal processing algorithms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.735309

Filename

735309