Title :
Fast orthogonal iteration adaptive algorithms for the generalized symmetric eigenproblem
Author_Institution :
Fachhochschule Furtwangen, Germany
fDate :
12/1/1998 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
