NDLI: On the convergence behavior of the LMS and the normalized LMS algorithms

Content Provider	IEEE Xplore Digital Library
Author	Slock, D.T.M.
Copyright Year	1991
Abstract	It is shown that the normalized least mean square (NLMS) algorithm is a potentially faster converging algorithm compared to the LMS algorithm where the design of the adaptive filter is based on the usually quite limited knowledge of its input signal statistics. A very simple model for the input signal vectors that greatly simplifies analysis of the convergence behavior of the LMS and NLMS algorithms is proposed. Using this model, answers can be obtained to questions for which no answers are currently available using other (perhaps more realistic) models. Examples are given to illustrate that even quantitatively, the answers obtained can be good approximations. It is emphasized that the convergence of the NLMS algorithm can be speeded up significantly by employing a time-varying step size. The optimal step-size sequence can be specified a priori for the case of a white input signal with arbitrary distribution.<>
Sponsorship	IEEE Signal Processing Society
Starting Page	2811
Ending Page	2825
Page Count	15
File Size	1524395
File Format	PDF
ISSN	1053587X
Volume Number	41
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Least squares approximation Convergence Steady-state Adaptive filters Signal processing algorithms Algorithm design and analysis Signal analysis Finite impulse response filter Signal design Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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