Linear least-square estimation algorithms involving correlated signal and noise

IEEE Transactions on Signal Processing

Volumn 53, Issue 11, 2005, Pages 4227-4235

  Fernández Alcalá, Rosa María ^a   Navarro Moren, Jesús ^a   Ruiz Molina, Juan Carlos ^a  

^a UNIVERSITY OF JAÉN   (Spain)

Author keywords

Correlated signal and noise; Covariance factorization; Least mean square methods; Recursive estimation

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; CORRELATION THEORY; FEEDBACK CONTROL; INTEGRAL EQUATIONS; PARTIAL DIFFERENTIAL EQUATIONS; SIGNAL FILTERING AND PREDICTION; THEOREM PROVING; VECTORS; WHITE NOISE;

COVARIANCE FACTORIZATION; FEEDBACK COMMUNICATIONS; LEAST MEAN SQUARE METHODS; RECURSIVE ESTIMATION;

SIGNAL DETECTION;

EID: 27744486979     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2005.857045     Document Type: Article

References (15)

1. A. Gelb, Applied Optimal Estimation. Cambridge, MA: MIT Press, 1989.
2. T. Kailath, A. Sayed, and B. Hassibi, Linear Estimation. Englewood Cliffs, NJ: Prentice-Hall, 2000.
3. H. Van Trees, Detection, Estimation, and Modulation Theory. Part I. New York: Wiley, 1968.
4. H. Kagiwada and R. Kalaba, "An initial value theory for Fredholm integral equation with semi-degenerate kernels," J. Assoc. Comput. Machinery, vol. 1, pp. 412-417, 1970.
5. S. Nakamori, "New design of linear discrete-time predictor using covariance information," Automatica, vol. 19, pp. 341-344, 1983.
6. M. Sugisaka, "The design of on-line least-squares estimators given covariance specifications via an imbedding method" Appl. Math. Comput., no. 13, pp. 55-85, 1983.
7. S. Nakamori, "New design of linear least-squares fixed-point smoother using covariance information in continuous systems," Int. J. Syst. Sci., vol. 21, no. 3, pp. 527-536, 1990.
8. S. Nakamori, "A new predictor using covariance information in linear continuous systems," Automatica, vol. 27, no. 6, pp. 1055-1058, 1991.
9. S. Nakamori, "Design of recursive fixed-point smoother using covariance information in linear discrete-time systems," Int. J. Syst. Sci., vol. 23, no. 12, pp. 2323-2334, 1992.
10. S. Nakamori, "New design of fixed-interval smoother using covariance information in linear stochastic continuous-time systems," Appl. Math. Comput., vol. 144, no. 2-3, pp. 557-567, 2003.
11. S. Nakamori, "New design of fixed-lag smoother using covariance information in linear discrete-time stochastic systems," Appl. Math. Comput., vol. 156, no. 2, pp. 415-426, 2004.
12. A. Baggeroer and H. L. Van Trees, "State variable analysis procedures," in Detection, Estimation, and Modulation Theory. Part II. New York: Wiley, 1971, pp. 286-327.
13. T. Kailath, R. Geesey, and H. Weinert, "Some relations among RKHS norms, Fredholm equations, and innovations representations," IEEE Trans. Inf. Theory, vol. IT-18, no. 3, pp. 341-348, May 1972.
14. W. Gardner, "A series solution to smoothing, filtering, and prediction problems involving correlated signal and noise," IEEE Trans. Inf. Theory, vol. IT-21, no. 6, pp. 698-699, Nov. 1975.
15. S. Nakamori, A. Hermoso-Carazo, J. Linares-Pérez, and M. Sánchez-Rodríguez, "Fixed-interval smoothing problem from uncertain observations with correlated signal and noise," Appl. Math. Comput., vol. 154, no. 1, pp. 239-255, 2004.