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  1. 研究論文

Performance Improvement of Variable Stepsize NLMS

https://nitech.repo.nii.ac.jp/records/4364
https://nitech.repo.nii.ac.jp/records/4364
e41f3c6d-6f7f-41e0-bac7-f1cc0dca1d7a
名前 / ファイル ライセンス アクション
E78-A_905.pdf 本文_fulltext (865.6 kB)
Copyright(c)1995 IEICE http://search.ieice.org/index.html
Item type 学術雑誌論文 / Journal Article(1)
公開日 2013-06-25
タイトル
タイトル Performance Improvement of Variable Stepsize NLMS
言語 en
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者 Tanpreeyachaya, Jirasak

× Tanpreeyachaya, Jirasak

en Tanpreeyachaya, Jirasak

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Takumi, Ichi

× Takumi, Ichi

en Takumi, Ichi

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Hata, Masayasu

× Hata, Masayasu

en Hata, Masayasu

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著者別名
姓名 内匠, 逸
書誌情報 en : IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

巻 E78-A, 号 8, p. 905-914, 発行日 1995-08-20
出版者
出版者 Institute of Electronics, Information and Communication Engineers
言語 en
ISSN
収録物識別子タイプ ISSN
収録物識別子 0916-8508
item_10001_source_id_32
収録物識別子タイプ NCID
収録物識別子 AA10826239
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
内容記述
内容記述タイプ Other
内容記述 Improvement of the convergence characteristics of the NLMS algorithm has received attention in the area of adaptive filtering. A new variable stepsize NLMS method, in which the stepsize is updated optimally by using variances of the measured error signal and the estimated noise, is proposed. The optimal control equation of the stepsize has been derived from a convergence characteristic approximation. A new condition to judge convergence is introduced in this paper to ensure the fastest initial convergence speed by providing precise timing to start estimating noise level. And further, some adaptive smoothing devices have been added into the ADF to overcome the saturation problem of the identification error caused by some random deviations. By the simulation, The initial convergence speed and the identification error in precise identification mode is improved significantly by more precise adjustment of stepsize without increasing in computational cost. The results are the best ever reported performanced. This variable stepsize NLMS-ADF also shows good effectiveness even in severe conditions, such as noisy or fast changing circumstances.
言語 en
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