Commenced in January 2007
Paper Count: 32451
The Performance Analysis of Error Saturation Nonlinearity LMS in Impulsive Noise based on Weighted-Energy Conservation
Abstract:This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1061711Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478
 X. Wang and H. V. Poor, "Joint channel estimation and symbol detection in rayleigh flat-fading channels with impulsive noise", IEEE Commun. Lett., vol. 1, no. 1, pp. 1921, Jan. 1997.
 S. R. Kim and A. Efron, "Adaptive robust impulsive noise filtering", IEEE Trans. Signal Process., vol. 43, no. 8, pp. 1855 1866, Aug. 1995.
 S. C. Chan and Y. X. Zou, "A recursive least m-estimate algorithm for robust adaptive filtering in impulsive noise: Fast algorithm and convergence performance analysis", IEEE Trans. Signal Process., vol. 52, no. 4, pp. 975991, April 2004.
 N. J. Bershad, "On error saturation nonlinearities for LMS adaptation", IEEE Trans. Acoust., Speech, Signal Process., vol. 36, no. 4, pp. 440452, April 1988.
 N. J. Bershad, "On weight update saturation nonlinearities in LMS adaptation", IEEE Trans. Acoust., Speech, Signal Process., vol. 38, no. 2, pp. 623630, Feb. 1990.
 H. Fan and R. Vemuri, "Robust adaptive algorithms for active noise and vibration control", Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on, pp. 11371140 vol.2, Apr 1990.
 O. Abu-Ella and B. El-Jabu, "Optimal robust adaptive LMS algorithm without adaptation step-size", Millimeter Waves,2008. GSMM 2008. Global Symposium on, pp. 249251, April 2008.
 N. J. Bershad and M. Bonnet, "Saturation effects in LMS adaptive echo cancellation for binary data", IEEE Trans. Signal Process., vol. 38, no. 10, pp. 16871696, Oct. 1990.
 N. J. Bershad, "On error saturation nonlinearities for LMS adaptation in impulsive noise, IEEE Trans. Signal Process., vol. 56, no. 9, pp. 45264530, Sep. 2008.
 B. Widrow and S. D. Strearns, Adaptive Signal Processing. Englewood Cliffs, NJ:Prentice-Hall, 1985.
 S. Haykin, Adaptive filter theory. Englewood Cliffs, NJ:Prentice-Hall, 2001.
 A. H. Sayed, Fundamentals of Adaptive Filtering. JohnWiley and Sons. Inc. Publication, 2003.
 T. Y. Al-Naffouri and A. H. Sayed, "Transient analysis of adaptive filters with error nonlinearities", IEEE Trans. Signal Process., vol. 51, no. 3, pp. 653663, March 2003.
 T. Y. Al-Naffouri and A. H. Sayed, "Adaptive filters with error nonlinearities: Mean-square analysis and optimum design", EURASIP Journal on Applied Signal Processing, pp. 192205, OCT. 2001.
 T. Y. Al-Naffouri and A. H. Sayed, "Transient analysis of datanormalized adaptive filters", IEEE Trans. Signal Process., vol. 51, no. 3, pp. 639652, March 2003.
 R. Price, "A usefull theorem for non-linear devices having Gaussian inputs", IRE Trans. Inf. Theory, vol. IT-4, pp. 6972, June 1958.
 R. Pawula, "A modified version of prices theorem", Information Theory, IEEE Transactions on, vol. 13, no. 2, pp. 285 288, Apr 1967.