Adaptive echo cancellation using least mean mixed-norm algorithm

A. Zerguine; C. F.N. Cowan; M. Bettayeb

doi:10.1109/78.575705

Adaptive echo cancellation using least mean mixed-norm algorithm

A. Zerguine^*
, C. F.N. Cowan
, M. Bettayeb

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

Abstract

A novel algorithm for echo cancellation is presented in this work. The algorithm consists of simultaneously applying the least mean square (LMS) algorithm to the near-end section of the echo canceller and the least mean fourth (LMF) algorithm to the far-end section. This new scheme results in a substantial performance improvement over the LMS algorithm and other algorithms.

Original language	English
Pages (from-to)	1340-1343
Number of pages	4
Journal	IEEE Transactions on Signal Processing
Volume	45
Issue number	5
DOIs	https://doi.org/10.1109/78.575705
State	Published - 1997

Bibliographical note

Funding Information:
Manuscript received October 25, 1996; revised January 2, 1997. This work was supported by King Fahd University of Petroleum and Minerals. The associate editor coordinating the review of this paper and approving it for publication was Prof. Georgios B. Giannakis. A. Zerguine is with the Department of Electronic and Electrical Engineering, Loughborough University, Loughborough, U.K. C. F. N. Cowan is with the Department of Electrical and Electronic Engineering, The Queen’s University of Belfast, Belfast, U.K. M. Bettayeb is with the Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia (e-mail: [email protected]). Publisher Item Identifier S 1053-587X(97)03349-7.

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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10.1109/78.575705

Cite this

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title = "Adaptive echo cancellation using least mean mixed-norm algorithm",

abstract = "A novel algorithm for echo cancellation is presented in this work. The algorithm consists of simultaneously applying the least mean square (LMS) algorithm to the near-end section of the echo canceller and the least mean fourth (LMF) algorithm to the far-end section. This new scheme results in a substantial performance improvement over the LMS algorithm and other algorithms.",

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note = "Funding Information: Manuscript received October 25, 1996; revised January 2, 1997. This work was supported by King Fahd University of Petroleum and Minerals. The associate editor coordinating the review of this paper and approving it for publication was Prof. Georgios B. Giannakis. A. Zerguine is with the Department of Electronic and Electrical Engineering, Loughborough University, Loughborough, U.K. C. F. N. Cowan is with the Department of Electrical and Electronic Engineering, The Queen{\textquoteright}s University of Belfast, Belfast, U.K. M. Bettayeb is with the Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia (e-mail: [email protected]). Publisher Item Identifier S 1053-587X(97)03349-7.",

year = "1997",

doi = "10.1109/78.575705",

language = "English",

volume = "45",

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journal = "IEEE Transactions on Signal Processing",

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AU - Bettayeb, M.

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AB - A novel algorithm for echo cancellation is presented in this work. The algorithm consists of simultaneously applying the least mean square (LMS) algorithm to the near-end section of the echo canceller and the least mean fourth (LMF) algorithm to the far-end section. This new scheme results in a substantial performance improvement over the LMS algorithm and other algorithms.

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M3 - Article

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JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 5

ER -

Adaptive echo cancellation using least mean mixed-norm algorithm

Abstract

Bibliographical note

ASJC Scopus subject areas

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