Density function approximation using reduced sufficient statistics for joint estimation of linear and nonlinear parameters

IEEE Transactions on Signal Processing

Volumn 47, Issue 8, 1999, Pages 2089-2099

  Iltis, Ronald A ^a  

^a University of California   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMMUNICATION CHANNELS (INFORMATION THEORY); COMPUTER SIMULATION; DOPPLER EFFECT; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY DENSITY FUNCTION; SPURIOUS SIGNAL NOISE; STATISTICAL METHODS;

ADDITIVE GAUSSIAN NOISE; AVERAGED SQUARED ERROR; CRAMER-RAO BOUND; HAAR BASIS SCALE FUNCTIONS; REDUCED SUFFICIENT STATISTICS;

SIGNAL PROCESSING;

EID: 0033171264     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.774741     Document Type: Article

References (18)

1. D. Lainiotis, "Partitioning: A unifying framework for adaptive systems. I. Estimation," Proc. IEEE, vol. 64, pp. 1126-1143, Aug. 1976.
2. H. Sorenson and D. Alspach, "Recursive Bayesian estimation using Gaussian sums," Automatica, vol. 7, pp. 465-479, 1971.
3. D. Alspach and H. Sorenson, "Nonlinear Bayesian estimation using Gaussian sum approximations," IEEE Trans. Automat. Contr., vol. AC-17, pp. 439-448, Aug. 1972.
4. A. Fuxjaeger and R. Iltis, "Adaptive parameter estimation using parallel Kalman filtering for spread-spectrum code and doppler tracking," IEEE Trans. Commun., vol. 42, pp. 2227-2230, June 1994.
5. R. Kulhavý, "A Bayes-closed approximation of recursive nonlinear estimation," Int. J. Adaptive Contr. Signal Process., vol. 4, pp. 271-285, July-Aug. 1990.
6. _, "Recursive nonlinear estimation: A geometric approach," Automatica, vol. 26, pp. 545-555, May 1990.
7. I. Daubechies, "Orthonormal bases of compactly supported wavelets," Commun. Pure Appl. Math., vol. 45, pp. 909-996, June 1988.
8. S. Mallat, "Multifrequency channel decompositions of images and wavelet models," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, pp. 2091-2110, Dec. 1989.
9. T. Kugarajah and Q. Zhang, "Multidimensional wavelet frames," IEEE Trans. Neural Networks, vol. 6, pp. 1552-1556, Nov. 1995.
10. Q. Zhang and A. Benveniste, "Wavelet networks," IEEE Trans. Neural Networks, vol. 3, pp. 889-898, Nov. 1992.
11. S. Kramer and H. Sorenson, "Recursive Bayesian estimation using piece-wise constant approximations," Automatica, vol. 24, pp. 789-801, 1988.
12. E. Masry, "Multiresolution analysis, wavelets, and probability density estimation," in Proc. 1994 IEEE Int. Symp. Inform. Theory, 1994, p. 39.
13. J. Mendel, Lessons in Digital Estimation Theory. Englewood Cliffs, NJ: Prentice-Hall, 1987.
14. B. Anderson and J. Moore, Optimal Filtering. Englewood Cliffs, NJ: Prentice-Hall, 1979.
15. F. Cohen, S. Kadambe, and G. Bourdreaux-Bartels, "Tracking of unknown nonstationary chirp signals using unsupervised clustering in the Wigner distribution space," IEEE Trans. Signal Processing, vol. 41, pp. 3085-3101, Nov. 1993.
16. P. Djuric and S. Kay, "Parameter estimation of chirp signals," IEEE Trans. Acoust., Speech, Signal Processing, vol. 38, pp. 2118-2126, Dec. 1990.
17. M. Karan, R. Williamson, and B. Anderson, "Performance of the maximum likelihood constant frequency estimator for frequency tracking," IEEE Trans. Signal Processing, vol. 42, pp. 2749-2767, Oct. 1994.
18. J. Proakis, Digital Communications. New York: McGraw-Hill, 1995.