Robust quasi-Newton adaptive filtering algorithms

IEEE Transactions on Circuits and Systems II: Express Briefs

Volumn 58, Issue 8, 2011, Pages 537-541

  Bhotto, Md Zulfiquar Ali ^a   Antoniou, Andreas ^a  

^a UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Adaptive filters; impulsive noise in adaptive filters; quasi Newton algorithms; robust adaptation algorithms

Indexed keywords

ADAPTIVE FILTERING; IMPULSE NOISE; INVERSE PROBLEMS;

ADAPTATION ALGORITHMS; ADAPTIVE FILTERING ALGORITHMS; ASYMPTOTICALLY STABLE; AUTOCORRELATION MATRIX; IMPULSIVE NOISE ENVIRONMENT; QUASI-NEWTON ALGORITHM; SPEED OF CONVERGENCE; STEADY-STATE MISALIGNMENTS;

ADAPTIVE FILTERS;

EID: 80051782356     PISSN: 15497747     EISSN: 15583791     Source Type: Journal    
DOI: 10.1109/TCSII.2011.2158722     Document Type: Article

References (19)

1. S. Koike, "Adaptive threshold nonlinear algorithm for adaptive filters with robustness against impulsive noise", IEEE Trans. Signal Process., vol. 45, no. 9, pp. 2391-2395, Sep. 1997.
2. J. F. Weng and S. H. Leung, "Adaptive nonlinear RLS algorithm for robust filtering in impulse noise", in Proc. IEEE Inter. Symp. Circuits Syst., Jun. 1997, pp. 2337-2340.
3. P. Petrus, "Robust Huber adaptive filter", IEEE Trans. Signal Process., vol. 47, no. 4, pp. 1129-1133, Apr. 1999.
4. Y. Zou, S. C. Chan, and T. S. Ng, "A recursive least M-estimate (RLM) adaptive filter for robust filtering in impulse noise", IEEE Signal Process. Lett., vol. 7, no. 11, pp. 324-326, Nov. 2000. (Pubitemid 32027069)
5. Y. Zou and S. C. Chan, "A robust quasi-Newton adaptive filtering algorithm for impulse noise suppression", in Proc. IEEE Inter. Symp. Circuits Syst., May 2001, pp. 677-680.
6. P. J. Rousseeuw and A. M. Leroy, Robust Regression and Outlier Detection. NewYork: Wiley, 1987.
7. M. L. R. de Campos and A. Antoniou, "A new quasi-Newton adaptive filtering algorithm", IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 44, no. 11, pp. 924-934, Nov. 1997. (Pubitemid 127768334)
8. P. S. R. Diniz, Adaptive Filtering: Algorithms and Practical Implementation, 3rd ed. NewYork: Springer-Verlag, 2008.
9. A. P. Liavas and P. A. Regalia, "On the numerical stability and accuracy of the conventional recursive least squares algorithm", IEEE Trans. Signal Process., vol. 47, no. 1, pp. 88-96, Jan. 1999.
10. G. E. Bottomley and S. T. Alexander, "A novel approach for stabilizing recursive least squares filters", IEEE Trans. Signal Process., vol. 39, no. 8, pp. 1770-1779, Aug. 1991. (Pubitemid 21674570)
11. A. Antoniou and W. S. Lu, Practical Optimization. New York: Springer-Verlag, 2007.
12. R. Fletcher, Practical Methods of Optimization. Hoboken, NJ: Wiley, 1980.
13. S. Werner, J. A. Apolinario, M. L. R. de Campos, and P. S. R. Diniz, "Low complexity constrained affine-projection algorithms", IEEE Trans. Signal Process., vol. 53, no. 12, pp. 4545-4555, Dec. 2005. (Pubitemid 41800391)
14. P. S. R. Diniz and S. Werner, "Set-membership binormalized data-reusing LMS algorithms", IEEE Trans. Signal Process., vol. 51, no. 1, pp. 124-134, Jan. 2003.
15. S. Werner and P. S. R. Diniz, "Set-membership affine projection algorithm", IEEE Signal Process. Lett., vol. 8, no. 8, pp. 231-235, Aug. 2001. (Pubitemid 32733162)
16. M. Z. A. Bhotto and A. Antoniou, "Improved quasi-Newton adaptive filtering algorithm", IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 57, no. 8, pp. 2109-2118, Aug. 2010.
17. S. C. Chan and Y. Zou, "A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: Fast algorithm and convergence analysis", IEEE Trans. Signal Process., vol. 52, no. 4, pp. 975-991, Apr. 2004.
18. L. R. Vega, H. Rey, J. Benesty, and S. Tressens, "A fast robust recursive least-squares algorithm", IEEE Trans. Signal Process., vol. 57, no. 3, pp. 1209-1216, Mar. 2009.
19. P. Z. Peebles, Probability, Random Variables and Random Signal Principles. NewYork: McGraw-Hill, 2000.