Title :
A note on the convergence analysis of LMS adaptive filters with Gaussian data
Author :
Foley, J.B. ; Boland, F.M.
Author_Institution :
Dept. of Microelectron. & Electr. Eng., Trinity Coll., Dublin, Ireland
fDate :
7/1/1988 12:00:00 AM
Abstract :
Necessary and sufficient conditions for the convergence of LMS (least-mean-squares) adaptive filters with Gaussian data have been established by L.L. Horowitz and K.D. Senne (1981), with the recent support of A. Feuer and E. Weinstein (1985). A feature of both of these studies is the necessity to investigate bounds on the roots of rather unwieldy characteristic equations. The authors show how such an investigation can be avoided through the use of a theorem of F. R. Gantmacher (1959). In formally applying this theorem, similar results to those of the above studies are obtained in a precise and straightforward manner
Keywords :
convergence; filtering and prediction theory; least squares approximations; Gaussian data; LMS adaptive filters; convergence analysis; Acoustic noise; Adaptive filters; Adaptive signal processing; Convergence; Covariance matrix; Equations; Gaussian noise; Least squares approximation; Noise cancellation; Signal processing algorithms; Sufficient conditions;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on