A new quasi-newton adaptive filtering algorithm

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing

Volumn 44, Issue 11, 1997, Pages 924-934

  De Campos, Marcello L R ^a  

^a MILITARY INSTITUTE OF ENGINEERING   (Brazil)

Author keywords

Adaptive filters; Optimization algorithms; Quantization effects

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; CORRELATION METHODS; DIGITAL ARITHMETIC; DIGITAL FILTERS; OPTIMIZATION;

NEWTON TYPE ALGORITHMS; QUANTIZATION EFFECTS;

ADAPTIVE FILTERING;

EID: 0031269409     PISSN: 10577130     EISSN: None     Source Type: Journal    
DOI: 10.1109/82.644046     Document Type: Article

References (25)

1. S. Ljung and L. Ljung, "Error propagation properties of recursive leastsquares adaptation algorithms," Automatica, vol. 21, no. 2, pp. 157-167, 1985.
2. D. T. Slock and T. Kailath, "Numerically stable fast transversal filters for recursive least squares adaptive filtering," IEEE Trans. Signal Processing, vol. 39, pp. 92-114, Jan. 1991.
3. M. H. Verhaegen, "Round-off error propagation in four generallyapplicable, recursive, least-squares estimation schemes," Automatica, vol. 25, no. 3, pp. 437-44, 1989.
4. G. E. Bottomley and S. T. Alexander, "A novel approach for stabilizing recursive least squares filters," IEEE Trans. Signal Processing, vol. 39, pp. 1770-1779, Aug. 1991.
5. S. Haykin, Adaptive Filter Theory. Englewood Cliffs, NJ: PrenticeHall, 2nd ed., 1991.
6. E. Eleftheriou and D. D. Falconer, "Tracking properties and steady-state performance of RLS adaptive filter algorithms," IEEE Trans. Acoustics, Speech, Signal Processing, vol. ASSP34, pp. 1097-1110, Oct. 1986.
7. P. S. R. Diniz, M. L. R. de Campos, and A. Antoniou, "Analysis of LMSNewton adaptive filtering algorithms with variable convergence factor," IEEE Trans. Signal Processing, vol. 43, pp. 617-627, Mar. 1995.
8. M. L. R. de Campos and A. Antoniou, "A robust quasi-Newton adaptive filtering algorithm," in Proc. Int. Symp. Circuits Syst., London, England, 1994, pp. 229-232.
9. P. S. R. Diniz and L. W. P. Biscainho, "Optimal variable step size for the LMS/Newton algorithm with application to subband adaptive filtering," IEEE Trans. Signal Processing, vol. 40, pp. 2825-2829, Nov. 1992.
10. R. Fletcher, Practical Methods of Optimization. New York: Wiley, 2nd ed., 1987.
11. B. Widrow and S. D. Stearns, Adaptive Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1985.
12. J. J. Shynk, "Adaptive IIR filtering," IEEE Signal Processing Mag., vol. 6, pp. 4-21, Apr. 1989.
13. D. F. Marshall and W. K. Jenkins, "A fast quasi-Newton adaptive filtering algorithm," IEEE Trans. Signal Processing, vol. 40, pp. 1652-1662, July 1992.
14. M. L. R. de Campos, P. S. R. Diniz, and A. Antoniou, "Performance of LMS-Newton adaptation algorithms with variable convergence factor in nonstationary environments," in Proc. Int. Conf. Acoust., Speech, Signal Processing, Minneapolis, MN, 1993, pp. 392-395.
15. R. Fletcher, "A new approach to variable metric algorithms," Comput. J., vol. 13, pp. 317-322, 1970.
16. G. C. Goodwin and S. K. Sin, Adaptive Filtering Prediction and Control. Englewood-Cliffs, NJ: Prentice-Hall, 1984.
17. M. L. R. de Campos, M. G. Siqueira, A. Antoniou, and A. N. Willson Jr., "A QR-decomposition LMS-Newton adaptive filtering algorithm with variable convergence factor," in Proc. IEEE Pacific Rim Conf. Commun. Comput., Signal Processing, Victoria, Canada, 1993, pp. 350-353.
18. J. H. Wilkinson, The Algebraic Eigenvalue Problem. New York: Oxford Univ. Press, 1965.
19. P. Voltz and F. Kozin, "Almost-sure convergence of adaptive algorithms by projections," IEEE Trans. Automat. Contr., vol. 34, pp. 325-327, Mar. 1989.
20. T. Kailath, Linear Systems. Englewood Cliffs, NJ: Prentice-Hall, 1980.
21. F. R. Gantmacher, The Theory of Matrices, vol. II. New York: Chelsea, 1959.
22. G. Kubin, "Stabilization of the RLS algorithm in the absence of persistent excitation," in Proc. Int. Conf. Acoust., Speech, Signal Processing, New York, 1988, pp. 1369-1372.
23. D. T. Slock, "On the convergence behaviour of the LMS and the normalized LMS algorithms," IEEE Trans. Signal Processing, vol. 41, pp. 2811-2825, Sept. 1993.
24. G. Kubin, "Recursive algorithms for adaptive transversal filters: Opti-mality and time variance," Ph.D. dissertation, Univ. Technol., Vienna, Austria, June 1990.
25. S. Subramanian, M. L. R. de Campos, D. J. Shpak, and A. Antoniou, "A robust quasi-Newton adaptive filtering algorithm for indoor wireless communications," in Proc. Int. Conf. Signal Processing Applicat. Technol., Dallas, TX, 1994, pp. 328-333.