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A new variable step-size LMS algorithm with robustness to nonstationary noise

Zhang, Y, Chambers, JA, Wang, W, Kendrick, P and Cox, TJ (2007) A new variable step-size LMS algorithm with robustness to nonstationary noise In: ICASSP'07, 2007-04-15 - 2007-04-20, Hawaii, USA.

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Abstract

A new variable step-size least-mean-square (VSSLMS) algorithm is presented in this paper for applications in which the desired response contains nonstationary noise with high variance. The step size of the proposed VSSLMS algorithm is controlled by the normalized square Euclidean norm of the averaged gradient vector, and is henceforth referred to as the NSVSSLMS algorithm. As shown by the analysis and simulation results, the proposed algorithm has both fast convergence rate and robustness to high-variance noise signals, and performs better than Greenburg's sum method, which is a robust algorithm for applications with nonstationary noise. ©2007 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
AuthorsEmailORCID
Zhang, YUNSPECIFIEDUNSPECIFIED
Chambers, JAUNSPECIFIEDUNSPECIFIED
Wang, WUNSPECIFIEDUNSPECIFIED
Kendrick, PUNSPECIFIEDUNSPECIFIED
Cox, TJUNSPECIFIEDUNSPECIFIED
Date : 4 June 2007
Identification Number : https://doi.org/10.1109/ICASSP.2007.367095
Contributors :
ContributionNameEmailORCID
PublisherIEEE, UNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:43
Last Modified : 28 Mar 2017 14:43
URI: http://epubs.surrey.ac.uk/id/eprint/596103

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