Convergence Analysis of Quantizing Method with Correlated Gaussian Data (Special Section on Digital Signal Processing)
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概要
- 論文の詳細を見る
In this paper the normalized least mean square (NLMS) algorithm based on clipping input samples with an arbitrary threshold level is studied. The convergence characteristics of these clipping algorithms with correlated data are presented. In the clipping algorithm, the input samples are clipped only when the input samples are greater than or equal to the threshold level and otherwise the input samples are set to zero. The results of the analysis yield that the gain constant to ensure convergence, the speed of the convergence, and the misadjustment are functions of the threshold level. Furthermore an optimum threshold level is derived in terms of the convergence speed under the condition of the constant misadjustment.
- 社団法人電子情報通信学会の論文
- 1996-08-25
著者
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TAKAHASHI Kiyoshi
Department of Medicine, National Minami-Okayama Hospital
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Mori Shinsaku
Department Of Electrical And Electronics Engineering Nippon Institute Of Technology
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Mori Shinsaku
Department Of Electrical & Electronics Engineering Nippon Institute Of Technology
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Takahashi Kiyoshi
Department Of Internal Medicine Ii Okayama University Graduate School Of Medicine And Dentistry
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Kuroyanagi N
Tokyo Univ. Technol. Hachioji‐shi Jpn
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Kuroyanagi Noriyoshi
Katayanagi Research Institute Tokyo University Of Technology
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Kuroyanagi Noriyoshi
Faculty Of Engineering Chubu University
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Kuroyanagi Noriyoshi
Department Of Information Networks Tokyo Engineering University
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Mori Shinsaku
Department Of Electrical Engineering Keio University
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Takahashi K
Department Of Information Networks Tokyo Engineering University
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Takahashi Kiyoshi
Department Of Electrical And Electronic Engineering Tokyo Institute Of Technology
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Takahashi Kiyoshi
Department Of Agronomy Faculty Of Agriculture Tohoku University
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