Transactions of the Institute of Systems, Control and Information Engineers
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
An Adaptive Setting Method of Step-Size Parameter in NLMS Algorithms
Jiro MORIMOTOYoshikazu YAMAMOTOIkunori KOBAYASHINanayo FURUMOTOToshiaki TABUCHI
Author information
JOURNALS FREE ACCESS

1997 Volume 10 Issue 11 Pages 594-606

Details
Abstract

A major, and yet unresolved, problem has been the choice of the step-size in some parameter tracking algorithms. This paper presents an adaptive setting method of step-size parameter for tracking time-varying parameters when normalized least mean square (NLMS) algorithm is used. The usual method suggested by Benveniste et al is to adjust the step-size so as to minimize the performance measure defined by the mean squares of prediction error. The weak point of this method is that the performance measure converges only on a local minimum.
The main object of this paper is to give a solution for this problem. The solution obtained is that the performance measure converges on the global minimum through the minimization of another performance measure. As a result, the proposed algorithm becomes asymptotically optimal.
Numerical examples indicate acceptable performance of the proposed method.

Information related to the author
© The Institute of Systems, Control and Information Engineers
Previous article Next article
feedback
Top