Modified Clipped LMS Algorithm

<p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Lotfizad Mojtaba [verfasserIn] Yazdi Hadi Sadoghi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2005

Schlagwörter:	adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm

Übergeordnetes Werk:	In: EURASIP Journal on Advances in Signal Processing - SpringerOpen, 2008, (2005), 8, p 310205
Übergeordnetes Werk:	year:2005 ; number:8, p 310205

Links:	Link aufrufen Link aufrufen Journal toc Journal toc

Katalog-ID:	DOAJ002887517

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allfields	(DE-627)DOAJ002887517 (DE-599)DOAJ1c67580142b54ce08bd7b10ad1b98124 DE-627 ger DE-627 rakwb eng TK5101-6720 TK7800-8360 Lotfizad Mojtaba verfasserin aut Modified Clipped LMS Algorithm 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p< adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm Telecommunication Electronics Yazdi Hadi Sadoghi verfasserin aut In EURASIP Journal on Advances in Signal Processing SpringerOpen, 2008 (2005), 8, p 310205 (DE-627)534054277 (DE-600)2364203-8 16876180 nnns year:2005 number:8, p 310205 https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 kostenfrei http://dx.doi.org/10.1155/ASP.2005.1229 kostenfrei https://doaj.org/toc/1687-6172 Journal toc kostenfrei https://doaj.org/toc/1687-6180 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_161 GBV_ILN_170 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2522 AR 2005 8, p 310205
spelling	(DE-627)DOAJ002887517 (DE-599)DOAJ1c67580142b54ce08bd7b10ad1b98124 DE-627 ger DE-627 rakwb eng TK5101-6720 TK7800-8360 Lotfizad Mojtaba verfasserin aut Modified Clipped LMS Algorithm 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p< adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm Telecommunication Electronics Yazdi Hadi Sadoghi verfasserin aut In EURASIP Journal on Advances in Signal Processing SpringerOpen, 2008 (2005), 8, p 310205 (DE-627)534054277 (DE-600)2364203-8 16876180 nnns year:2005 number:8, p 310205 https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 kostenfrei http://dx.doi.org/10.1155/ASP.2005.1229 kostenfrei https://doaj.org/toc/1687-6172 Journal toc kostenfrei https://doaj.org/toc/1687-6180 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_161 GBV_ILN_170 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2522 AR 2005 8, p 310205
allfields_unstemmed	(DE-627)DOAJ002887517 (DE-599)DOAJ1c67580142b54ce08bd7b10ad1b98124 DE-627 ger DE-627 rakwb eng TK5101-6720 TK7800-8360 Lotfizad Mojtaba verfasserin aut Modified Clipped LMS Algorithm 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p< adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm Telecommunication Electronics Yazdi Hadi Sadoghi verfasserin aut In EURASIP Journal on Advances in Signal Processing SpringerOpen, 2008 (2005), 8, p 310205 (DE-627)534054277 (DE-600)2364203-8 16876180 nnns year:2005 number:8, p 310205 https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 kostenfrei http://dx.doi.org/10.1155/ASP.2005.1229 kostenfrei https://doaj.org/toc/1687-6172 Journal toc kostenfrei https://doaj.org/toc/1687-6180 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_161 GBV_ILN_170 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2522 AR 2005 8, p 310205
allfieldsGer	(DE-627)DOAJ002887517 (DE-599)DOAJ1c67580142b54ce08bd7b10ad1b98124 DE-627 ger DE-627 rakwb eng TK5101-6720 TK7800-8360 Lotfizad Mojtaba verfasserin aut Modified Clipped LMS Algorithm 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p< adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm Telecommunication Electronics Yazdi Hadi Sadoghi verfasserin aut In EURASIP Journal on Advances in Signal Processing SpringerOpen, 2008 (2005), 8, p 310205 (DE-627)534054277 (DE-600)2364203-8 16876180 nnns year:2005 number:8, p 310205 https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 kostenfrei http://dx.doi.org/10.1155/ASP.2005.1229 kostenfrei https://doaj.org/toc/1687-6172 Journal toc kostenfrei https://doaj.org/toc/1687-6180 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_161 GBV_ILN_170 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2522 AR 2005 8, p 310205
allfieldsSound	(DE-627)DOAJ002887517 (DE-599)DOAJ1c67580142b54ce08bd7b10ad1b98124 DE-627 ger DE-627 rakwb eng TK5101-6720 TK7800-8360 Lotfizad Mojtaba verfasserin aut Modified Clipped LMS Algorithm 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p< adaptive filter LMS algorithm clipped LMS algorithm modified clipped LMS algorithm Telecommunication Electronics Yazdi Hadi Sadoghi verfasserin aut In EURASIP Journal on Advances in Signal Processing SpringerOpen, 2008 (2005), 8, p 310205 (DE-627)534054277 (DE-600)2364203-8 16876180 nnns year:2005 number:8, p 310205 https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 kostenfrei http://dx.doi.org/10.1155/ASP.2005.1229 kostenfrei https://doaj.org/toc/1687-6172 Journal toc kostenfrei https://doaj.org/toc/1687-6180 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_161 GBV_ILN_170 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2522 AR 2005 8, p 310205
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title	Modified Clipped LMS Algorithm
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title_full	Modified Clipped LMS Algorithm
author_sort	Lotfizad Mojtaba
journal	EURASIP Journal on Advances in Signal Processing
journalStr	EURASIP Journal on Advances in Signal Processing
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author_browse	Lotfizad Mojtaba Yazdi Hadi Sadoghi
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format_se	Elektronische Aufsätze
author-letter	Lotfizad Mojtaba
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title_sort	modified clipped lms algorithm
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title_auth	Modified Clipped LMS Algorithm
abstract	<p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p<
abstractGer	<p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p<
abstract_unstemmed	<p<Abstract</p< <p<A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( <inline-formula<<graphic file="1687-6180-2005-310205-i1.gif"/<</inline-formula<) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.</p<
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title_short	Modified Clipped LMS Algorithm
url	https://doaj.org/article/1c67580142b54ce08bd7b10ad1b98124 http://dx.doi.org/10.1155/ASP.2005.1229 https://doaj.org/toc/1687-6172 https://doaj.org/toc/1687-6180
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