A Variable-Step LMS Algorithm Based on the Adaptive Noise Cancellation

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A variable step long LMS algorithm based on Bessel function was put forward, which established the functional relationship between the step size factor and the error signal. And this algorithm would be applied to the adaptive noise canceller in order to improve the ability of the algorithm of uncorrelated noise suppression. This algorithm has a larger step-size during initial convergence stage or unknown system parameters change in order to get a faster convergence time and tracking speed. Moreover, and it adjusts small step-size to achieve a very small steady-state maladjustment noise after the convergence of the algorithm.

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375-379

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] S Haykin. Adaptive Filter Theory. 4th edn. NJ: Prentice-Hall, (2002).

Google Scholar

[2] B Widrow, SD Stearns. Adaptive Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, (1985).

Google Scholar

[3] Sock, D.T.M. On the Convergence Behavior of the LMS and the Normalized LMS Algorithms. IEEE Trans. on Signal Processing, 41(9), 2811–2825, (1993).

DOI: 10.1109/78.236504

Google Scholar

[4] J. Benesty, H. Rey, L.R. Vega, S. Tressens. A nonparametric VSS NLMS algorithm. IEEE Signal Process. Lett, 13(10): 581–584, (2006).

DOI: 10.1109/lsp.2006.876323

Google Scholar

[5] R. H. Kwong, E.W. Johnston. A variable step size LMS algorithm. IEEE Trans. Signal Process. 40(6): 1633–1642 . (1992).

DOI: 10.1109/78.143435

Google Scholar

[6] H.J. Butterweck. Iterative analysis of the state-space weight fluctuations in LMS-type adaptive filters. IEEE Trans. on Signal Processing, vol. 47, pp.2558-2561, Sept. (1999).

DOI: 10.1109/78.782205

Google Scholar

[7] Marcos S, Mcchi O. Tracking capability of the least mean square algorithm: application to an asynchrDn0us echo canceller. IEEE Trans on Acoust Speech,Signal Processing, 35(11): 1570—157, (1987).

DOI: 10.1109/tassp.1987.1165084

Google Scholar

[8] OW Kwong, ED Johnston. A variable step-size LMS algorithm. IEEE Trans Signal Processing. 40(7), 1633–1642. doi: 10. 110978. 143435, (1992).

DOI: 10.1109/78.143435

Google Scholar

[9] C. Bao, P. Sas, and H.V. Brussel. Adaptive active control of noise in 3-D reverberant enclosure. J. SoundVibr, Mar. vol. 161, no. 3, pp.501-514, (1993).

DOI: 10.1006/jsvi.1993.1088

Google Scholar

[10] M. H. Costa, J. Bermudez. A robust variable step size algorithm for LMS adaptive filters. Proc. EEE Int. Conf. Acoust. Speech Signal Process, vol. 3, p.93–96, (2006).

DOI: 10.1109/icassp.2006.1660598

Google Scholar

[11] Fang Xiao-ming. Analysis and Research on the methods of adaptive noise cancellation in Communication. Anhui University Of Science And Technology . The library of Anhui University of Science And Technology. 39-65. (2009).

Google Scholar