Theoretic analysis of the γ-LMS algorithm

Wen-Rong Wu; Po Cheng Chen

doi:10.1109/APCCAS.1994.514580

Theoretic analysis of the γ-LMS algorithm

Wen-Rong Wu^*, Po Cheng Chen

^*Corresponding author for this work

Department of Electrical and Computer Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher [1] suggested the γ-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the γ-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulation are provided to show the accuracy of our theoretical results.

Original language	English
Pages	382-387
Number of pages	6
DOIs	https://doi.org/10.1109/APCCAS.1994.514580
State	Published - 5 Dec 1994
Event	Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems - Taipei, Taiwan Duration: 5 Dec 1994 → 8 Dec 1994

Conference

Conference	Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems
City	Taipei, Taiwan
Period	5/12/94 → 8/12/94

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10.1109/APCCAS.1994.514580

Cite this

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title = "Theoretic analysis of the γ-LMS algorithm",

abstract = "The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher [1] suggested the γ-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the γ-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulation are provided to show the accuracy of our theoretical results.",

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year = "1994",

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doi = "10.1109/APCCAS.1994.514580",

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AB - The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher [1] suggested the γ-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the γ-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulation are provided to show the accuracy of our theoretical results.

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T2 - Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems

Y2 - 5 December 1994 through 8 December 1994

ER -

Theoretic analysis of the γ-LMS algorithm

Abstract

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