Almost-sure convergence of the continuous-time LMS algorithm

The authors consider the stability properties of the conventional continuous-time least mean square algorithm. The algorithm for the case of stationary ergodic inputs is investigated and a necessary and sufficient condition for exponential almost-sure convergence is presented. This condition is show...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on signal processing Vol. 40; no. 2; pp. 395 - 401
Main Authors Voltz, P.J., Kozin, F.
Format Journal Article
LanguageEnglish
Published IEEE 01.02.1992
Subjects
Adaptive arrays
Adaptive control
Autocorrelation
Convergence
Least squares approximation
Stability
Sufficient conditions
System identification
Vectors
Online AccessGet full text
ISSN1053-587X
DOI10.1109/78.124949

Cover

More Information
Summary:The authors consider the stability properties of the conventional continuous-time least mean square algorithm. The algorithm for the case of stationary ergodic inputs is investigated and a necessary and sufficient condition for exponential almost-sure convergence is presented. This condition is shown to be less restrictive than the well-known persistency of excitation condition. Also, the authors point out and clarify an apparently common error regarding the connections between persistency of excitation and positive definite autocorrelation in stationary ergodic vector waveforms.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1053-587X
DOI:10.1109/78.124949