Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm
Abstract
Maximum correntropy criterion (MCC) based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD) error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.
Keywords:
Maximum correntropy criteria, adaptive filter, variable step size, mean square deviationDownloads
References
S. Haykin, Adaptive filtering theory, Prentice-Hall, New York, NY, USA, 1996.
J. C. Principe, Information theoretic learning: Renyi’s entropy and kernel perspectives, Springer Verlag, Berlin, Germany, 2010 DOI: https://doi.org/10.1007/978-1-4419-1570-2
W. Liu, P. P. Pokharel, and J. C. Principe, “Correntropy: Properties, and applications in non-Gaussian signal processing”, IEEE Trans. Signal Process., Vol. 55, No. 11, pp. 5286–5298, 2007 DOI: https://doi.org/10.1109/TSP.2007.896065
A. Singh, J. C. Principe, “Using correntropy as a cost function in adaptive filters”, International Joint Conference on Neural Networks, Atlanta, USA, pp. 2950–2955, June 14-19, 2009 DOI: https://doi.org/10.1109/IJCNN.2009.5178823
B. Chen, L. Xing, J. Liang, N. Zheng, J. C. Príncipe, “Steady-state mean-square error analysis for adaptive filtering under the maximum correntropy criterion”, IEEE Signal Processing Letters, Vol. 21, No. 7, pp. 880-884, 2014 DOI: https://doi.org/10.1109/LSP.2014.2319308
L. Shi, Y. Lin, “Convex combination of adaptive filters under the maximum correntropy criterion in impulsive interference,” IEEE Signal Processing Letters, Vol. 21, No. 11, pp. 1385-1388, 2014 DOI: https://doi.org/10.1109/LSP.2014.2337899
S. Zhao, B. Chen, J. C. Principe, “An adaptive kernel width update for correntropy” , The 2012 International Joint Conference on Neural networks, Brisbane, Australia, pp. 1–5, June 10-15, 2012 DOI: https://doi.org/10.1109/IJCNN.2012.6252495
R. H. Kwong, E. W. Johnston, “A variable step size LMS algorithm”, IEEE Transactions on Signal Processing, Vol. 40,No. 7, pp. 1633-1642, 1992 DOI: https://doi.org/10.1109/78.143435
H. C. Shin, A. H. Sayed, W. J. Song, “Variable step-size NLMS and affine projection algorithms”, IEEE Signal Processing Letters, Vol. 11, No. 2, pp. 132-135, 2004 DOI: https://doi.org/10.1109/LSP.2003.821722
X. D. Luo, Z. H. Jia, Q. Wang, “A new variable step size LMS adaptive filtering algorithm”, Acta Electronica Sinica, Vol. 34, No. 6, pp. 1123-1126, 2006
A. H. Sayed, Adaptive filters, John Wiley & Sons, 2008 DOI: https://doi.org/10.1002/9780470374122
W. Ma, H. Qua, G. Gui, L. Xu, J. Zhaoa, B. Chen, “Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments”, Journal of the Franklin Institute, Vol. 352, No. 7, pp. 2708-2727, 2015 DOI: https://doi.org/10.1016/j.jfranklin.2015.03.039
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