The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'algorithme des moindres carrés moyens normalisés individuellement (INLMS) est proposé comme algorithme adaptatif adapté au traitement en virgule fixe. La propriété de convergence de l’algorithme INLMS n’est cependant pas encore suffisamment analysée. Cet article dérive d'abord une équation décrivant la propriété de convergence en exploitant la technique d'expression de l'algorithme INLMS sous la forme d'un filtre à réponse impulsionnelle infinie (RII) de premier ordre. Selon l'équation ainsi dérivée, le processus décroissant de l'erreur d'estimation est représenté comme la réponse d'une autre expression de filtre IIR. En utilisant la représentation, cet article dérive ensuite la condition de convergence de l'algorithme INLMS comme la plage de tailles de pas créant un filtre de chemin bas de ce dernier filtre IIR. Cet article dérive également la taille de pas maximisant la vitesse de convergence comme coefficient maximum de ce dernier filtre IIR et clarifie enfin la plage de taille de pas recommandée dans la conception pratique du système.
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Kensaku FUJII, Juro OHGA, "Analysis on Convergence Property of INLMS Algorithm Suitable for Fixed Point Processing" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 8, pp. 1539-1544, August 2000, doi: .
Abstract: The individually normalized least mean square (INLMS) algorithm is proposed as an adaptive algorithm suitable for the fixed point processing. The convergence property of the INLMS algorithm, however, is not yet analyzed enough. This paper first derives an equation describing the convergence property by exploiting the technique of expressing the INLMS algorithm as a first order infinite impulse response (IIR) filter. According to the equation derived thus, the decreasing process of the estimation error is represented as the response of another IIR filter expression. By using the representation, this paper second derives the convergence condition of the INLMS algorithm as the range of the step size making a low path filter of the latter IIR filter. This paper also derives the step size maximizing the convergence speed as the maximum coefficient of the latter IIR filter and finally clarifies the range of the step size recommended in the practical system design.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_8_1539/_p
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@ARTICLE{e83-a_8_1539,
author={Kensaku FUJII, Juro OHGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Analysis on Convergence Property of INLMS Algorithm Suitable for Fixed Point Processing},
year={2000},
volume={E83-A},
number={8},
pages={1539-1544},
abstract={The individually normalized least mean square (INLMS) algorithm is proposed as an adaptive algorithm suitable for the fixed point processing. The convergence property of the INLMS algorithm, however, is not yet analyzed enough. This paper first derives an equation describing the convergence property by exploiting the technique of expressing the INLMS algorithm as a first order infinite impulse response (IIR) filter. According to the equation derived thus, the decreasing process of the estimation error is represented as the response of another IIR filter expression. By using the representation, this paper second derives the convergence condition of the INLMS algorithm as the range of the step size making a low path filter of the latter IIR filter. This paper also derives the step size maximizing the convergence speed as the maximum coefficient of the latter IIR filter and finally clarifies the range of the step size recommended in the practical system design.},
keywords={},
doi={},
ISSN={},
month={August},}
Copier
TY - JOUR
TI - Analysis on Convergence Property of INLMS Algorithm Suitable for Fixed Point Processing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1539
EP - 1544
AU - Kensaku FUJII
AU - Juro OHGA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2000
AB - The individually normalized least mean square (INLMS) algorithm is proposed as an adaptive algorithm suitable for the fixed point processing. The convergence property of the INLMS algorithm, however, is not yet analyzed enough. This paper first derives an equation describing the convergence property by exploiting the technique of expressing the INLMS algorithm as a first order infinite impulse response (IIR) filter. According to the equation derived thus, the decreasing process of the estimation error is represented as the response of another IIR filter expression. By using the representation, this paper second derives the convergence condition of the INLMS algorithm as the range of the step size making a low path filter of the latter IIR filter. This paper also derives the step size maximizing the convergence speed as the maximum coefficient of the latter IIR filter and finally clarifies the range of the step size recommended in the practical system design.
ER -