New results on convergence of the discrete-time LMS algorithm applied to narrowband adaptive arrays

The discrete-time, Least-Mean-Squares (LMS) algorithm is often proposed for application to adaptive antenna arrays. In analyzing the mean-square error performance of LMS, however, previous results in the open literature have generally employed approximations which are valid only in the limit for ver...

Full description

Saved in:
Bibliographic Details
Published in1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes pp. 1166 - 1167
Main Authors Senne, K. D., Horowitz, L. L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.1978
Subjects
Adaptive arrays
Approximation algorithms
Convergence
Iterative algorithms
Laboratories
Least squares approximation
Narrowband
Phased arrays
Sensor arrays
Stochastic processes
Online AccessGet full text
DOI10.1109/CDC.1978.268118

Cover

More Information
Summary:The discrete-time, Least-Mean-Squares (LMS) algorithm is often proposed for application to adaptive antenna arrays. In analyzing the mean-square error performance of LMS, however, previous results in the open literature have generally employed approximations which are valid only in the limit for very slow adaptation in an essentially stationary environment. In this paper we apply an exact mean-square error analysis for the application of discrete-time LMS to narrow-band adaptive arrays. The results provide considerable insight into the transient response of LMS under conditions of rapid adaptation, which is of importance in many practical applications.
DOI:10.1109/CDC.1978.268118