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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Algoritma segiempat sama terkecil ternormal secara individu (INLMS) dicadangkan sebagai algoritma penyesuaian yang sesuai untuk pemprosesan titik tetap. Sifat penumpuan algoritma INLMS, bagaimanapun, belum cukup dianalisis. Kertas kerja ini mula-mula menghasilkan persamaan yang menerangkan sifat penumpuan dengan mengeksploitasi teknik menyatakan algoritma INLMS sebagai penapis tindak balas impuls tak terhingga (IIR) tertib pertama. Mengikut persamaan yang diperolehi dengan itu, proses penurunan ralat anggaran diwakili sebagai tindak balas bagi ungkapan penapis IIR yang lain. Dengan menggunakan perwakilan, kertas kedua ini memperoleh keadaan penumpuan algoritma INLMS sebagai julat saiz langkah yang membuat penapis laluan rendah penapis IIR yang terakhir. Kertas ini juga memperoleh saiz langkah yang memaksimumkan kelajuan penumpuan sebagai pekali maksimum penapis IIR yang terakhir dan akhirnya menjelaskan julat saiz langkah yang disyorkan dalam reka bentuk sistem praktikal.
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Salinan
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
Salinan
@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},}
Salinan
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 -