Equation for Brief Evaluation of the Convergence Rate of the Normalized LMS Algorithm

Kensaku FUJII; Juro OHGA

Equation for Brief Evaluation of the Convergence Rate of the Normalized LMS Algorithm

Kensaku FUJII, Juro OHGA

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This paper presents an equation capable of briefly evaluating the length of white noise sequence to be sent as a training signal. The equation is formulated by utilizing the formula describing the convergence property, which has been derived from the IIR filter expression of the NLMS algorithm. The result revealed that the length is directly proportional to I/[K(2-K)] where K is a step gain and I is the number of the adaptive filter taps.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E76-A No.12 pp.2048-2051

Publication Date: 1993/12/25

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Type of Manuscript: Special Section LETTER (Special Section of Letters Selected from the 1993 IEICE Fall Conference)

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Kensaku FUJII, Juro OHGA, "Equation for Brief Evaluation of the Convergence Rate of the Normalized LMS Algorithm" in IEICE TRANSACTIONS on Fundamentals, vol. E76-A, no. 12, pp. 2048-2051, December 1993, doi: .
Abstract: This paper presents an equation capable of briefly evaluating the length of white noise sequence to be sent as a training signal. The equation is formulated by utilizing the formula describing the convergence property, which has been derived from the IIR filter expression of the NLMS algorithm. The result revealed that the length is directly proportional to I/[K(2-K)] where K is a step gain and I is the number of the adaptive filter taps.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e76-a_12_2048/_p

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@ARTICLE{e76-a_12_2048,
author={Kensaku FUJII, Juro OHGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Equation for Brief Evaluation of the Convergence Rate of the Normalized LMS Algorithm},
year={1993},
volume={E76-A},
number={12},
pages={2048-2051},
abstract={This paper presents an equation capable of briefly evaluating the length of white noise sequence to be sent as a training signal. The equation is formulated by utilizing the formula describing the convergence property, which has been derived from the IIR filter expression of the NLMS algorithm. The result revealed that the length is directly proportional to I/[K(2-K)] where K is a step gain and I is the number of the adaptive filter taps.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - Equation for Brief Evaluation of the Convergence Rate of the Normalized LMS Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2048
EP - 2051
AU - Kensaku FUJII
AU - Juro OHGA
PY - 1993
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E76-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 1993
AB - This paper presents an equation capable of briefly evaluating the length of white noise sequence to be sent as a training signal. The equation is formulated by utilizing the formula describing the convergence property, which has been derived from the IIR filter expression of the NLMS algorithm. The result revealed that the length is directly proportional to I/[K(2-K)] where K is a step gain and I is the number of the adaptive filter taps.
ER -