Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms

Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms

博士 === 元智大學 === 電機工程學系 === 101 === Numerous variable step-size and variable regularization algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This thesis proposes new nonparametric time-domain variable step-size normali...

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Main Authors: Hsu-Chang Huang, 黃旭章
Other Authors: Junghsi Lee
Format: Others
Language:en_US
Online Access:http://ndltd.ncl.edu.tw/handle/42422157543841638980
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spelling ndltd-TW-101YZU054420452016-03-18T04:41:49Z http://ndltd.ncl.edu.tw/handle/42422157543841638980 Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms 可變步階及可變調整參數之適應性濾波器演算法 Hsu-Chang Huang 黃旭章 博士 元智大學 電機工程學系 101 Numerous variable step-size and variable regularization algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This thesis proposes new nonparametric time-domain variable step-size normalized least mean-square (VSS-NLMS) and variable-regularization NLMS (VR-NLMS) algorithms. The VSS-NLMS employs the mean-square error (MSE) and the estimated system noise power to control the step-size update, and the VR-NLMS uses the input signal power, MSE and the estimated system noise power to control the variable regularization parameter. Extending the ideas of our VSS-NLMS algorithm, this thesis also presents a variable step-size control method for the partitioned frequency-domain block LMS (PFBLMS) adaptive filter. Junghsi Lee 李仲溪 學位論文 ; thesis 99 en_US
collection NDLTD
language en_US
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sources NDLTD
description 博士 === 元智大學 === 電機工程學系 === 101 === Numerous variable step-size and variable regularization algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This thesis proposes new nonparametric time-domain variable step-size normalized least mean-square (VSS-NLMS) and variable-regularization NLMS (VR-NLMS) algorithms. The VSS-NLMS employs the mean-square error (MSE) and the estimated system noise power to control the step-size update, and the VR-NLMS uses the input signal power, MSE and the estimated system noise power to control the variable regularization parameter. Extending the ideas of our VSS-NLMS algorithm, this thesis also presents a variable step-size control method for the partitioned frequency-domain block LMS (PFBLMS) adaptive filter.
author2 Junghsi Lee
author_facet Junghsi Lee
Hsu-Chang Huang
黃旭章
author Hsu-Chang Huang
黃旭章
spellingShingle Hsu-Chang Huang
黃旭章
Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
author_sort Hsu-Chang Huang
title Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
title_short Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
title_full Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
title_fullStr Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
title_full_unstemmed Variable Step-Size and Variable Regularization Adaptive Filtering Algorithms
title_sort variable step-size and variable regularization adaptive filtering algorithms
url http://ndltd.ncl.edu.tw/handle/42422157543841638980
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AT huángxùzhāng kěbiànbùjiējíkěbiàndiàozhěngcānshùzhīshìyīngxìnglǜbōqìyǎnsuànfǎ
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