Adaptive Recovery of a Chirped Sinusoid in Noise Part 1: Performance of the RLS Algorithm

IEEE Transactions on Signal Processing

Volumn 39, Issue 3, 1991, Pages 583-594

  Bershad, Neil J ^b  

^a CNRS   (France)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL TECHNIQUES--LEAST SQUARES APPROXIMATIONS; NOISE, SPURIOUS SIGNAL--ANALYSIS;

RECURSIVE LEAST SQUARES ALGORITHMS;

SIGNAL PROCESSING;

EID: 0026118465     PISSN: 1053587X     EISSN: 19410476     Source Type: Journal    
DOI: 10.1109/78.80878     Document Type: Article

References (17)

1. C. F. N. Cowan and P. M. Grant, Eds., Adaptive Filters. Englewood Cliffs, NJ: Prentice-Hall, 1985.
2. B. Widrow and S. D. Stearns, Adaptive Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1985.
3. M. G. Bellanger, Adaptive Digital Filters and Signal Analysis. New York: Marcel Dekker, 1987.
4. S. Haykin, Adaptive Filter Theory. Englewood Cliffs, NJ: Prentice-Hall, 1986.
5. F. Ling and J. G. Proakis, “Nonstationary learning characteristics of least squares adaptive estimation algorithms,” in Proc. ICASSP, 1984, 3.7.1-4.
6. O. Macchi, “Optimization of adaptive identification for time-varying filters,” IEEE Trans. Automat. Contr., vol. 31, no. 3, pp. 253–287, Mar. 1986.
7. E. Eleftheriou and D. D. Falconer, “Tracking properties and steady-state performance of RLS adaptive filter algorithms,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 34, no. 5, pp. 1097–1109, Oct. 1986.
8. S. McLaughlin, B. Mulgrew, and C. F. N. Cowan, “Performance comparison of least squares and least mean squares algorithms as HF channel estimators,” in Proc. ICASSP (Dallas, TX), Apr. 1987, pp. 49.2.1-4.
9. N. J. Bershad, P. L. Feintuch, F. A. Reed, and B. Fisher, “Tracking characteristics of the LMS adaptive line enhancer-response to a linear chirp signal in noise,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 28, no. 5, pp. 504–516, Oct. 1980.
10. A. Benveniste, “Design of adaptive algorithms for the tracking of time-varying systems, J. Adaptive Contr., Signal Processing, vol. 1, pp. 3–29, 1987.
11. O. Macchi and E. Eweda, “Compared speed and accuracy of the RLS and LMS algorithms with constant forgetting factors,” APII, vol. 22, pp. 255–267, 1988.
12. S. Marcos and O. Macchi, “Tracking capability of the least mean square algorithm: Application to an asynchronous echo canceller,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 35, no.11, dd. 1570–1578. 1987.
13. S. Gunnarsson and L. Ljung, “Frequency domain tracking characteristics of adaptive algorithms,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, no. 7, pp. 1072–1089, 1989.
14. E. Eweda and O. Macchi, “Tracking error bounds of adaptive nonstationary filtering,” Automatica, vol. 21, no. 3, pp. 293–302, 1985.
15. N. J. Bershad and O. Macchi, “Adaptive recovery of a chirped sinusoid in noise, Part 2: Performance of the LMS algorithm,” this issue, 595–602.
16. O. Macchi and N. J. Bershad, “Lag fluctuation misadjustment—addendum to ‘Adaptive recovery of a chirped sinusoid in noise, Part 1: Performance of the RLS algorithm’,” Laboratoire des Signaux and Systemes, CNRS, Gif-sur-Yvette, France, Tech. Rep., May 1989.
17. O. Macchi, “Optimisation du Gain d’une Boucle a Verrouillage de Phase en Mode de Pursuite,” in Proc. 10th GRETSI Colloquium (Nice, France), 1985, pp. 545–550.