Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm
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.
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
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
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
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
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
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
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
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
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
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
PDF Downloads 175
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.