Convergence Models for Lattice Joint Process Estimators and Least Squares Algorithms

IEEE Transactions on Acoustics, Speech, and Signal Processing

Volumn 31, Issue 2, 1983, Pages 415-425

  Honig, Michael L ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING - ALGORITHMS;

DIGITAL LATTICE FILTERS; KALMAN ALGORITHMS; LATTICE JOINT PROCESS; LEAST SQUARES ALGORITHMS;

ELECTRIC FILTERS, DIGITAL;

EID: 0020737493     PISSN: 00963518     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASSP.1983.1164084     Document Type: Article

References (19)

1. M. L. Honig and D. G. Messerschmitt, “Convergence properties of an adaptive digital lattice filter,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, pp. 642-653, June 1981.
2. M. L. Honig, “Performance of FIR adaptive filters using recursive algorithms,” Ph.D. dissertation, Univ. California, Berkeley, Apr. 1981.
3. M. L. Honig and D. G. Messerschmitt, “Comparison of LS and LMS lattice predictor algorithms using two performance criteria,” submitted to IEEE Trans. Acoust., Speech, Signal Processing.
4. L. J. Griffiths, “A continuously-adaptive filter implemented as a lattice structure,” in Proc. 1977 IEEE ICASSP, Hartford, CT, May 1977, pp. 683-686.
5. J. Makhoul, “A class of all-zero lattice digital filters: Properties and applications,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-26, pp. 304-314, Aug. 1978.
6. J. Makhoul and R. Viswanathan, “Adaptive lattice methods for linear prediction,” in Proc. 1978 IEEE ICASSP, Tulsa, OK, pp. 83-86.
7. E. H. Satorius and S. T. Alexander, “Channel equalization using adaptive lattice algorithms,” IEEE Trans. Commun., vol. COM-27, pp. 899-905, June 1979.
8. D. Godard, “Channel equalization using Kalman filter for fast data transmission,” IBM J. Res. Develop., pp. 267-273, May 1974.
9. D. D. Falconer and L. Ljung, “Application of fast Kalman estimation to adaptive equalization,” IEEE Trans. Commun., vol. COM-26, pp. 1439-1446, Oct. 1978.
10. E. H. Satorius and M. J. Shensa, “On the application of recursive least squares methods to adaptive processing,” presented at Int. Workshop Appl. Adaptive Contr., Yale Univ., New Haven, CT, Aug. 1979.
11. Lennart Ljung, Martin Morf, and David Falconer, “Fast calculation of gain matrices for recursive estimation schemes,” Int. J. Contr., vol. 27, no. 1, pp. 1-19, 1978.
12. M. Morf, D. T. Lee, J. R. Nickolls, and A. Vieira, “A classification of algorithms for ARMA models and ladder realizations,” in Proc. 1977 IEEE Conf. Acoust., Speech, Signal Processing, Hartford, CT, April. 1977, pp. 13-19.
13. M. Morf and D. Lee, “Recursive least squares ladder forms for fast parameter tracking,” in Proc. 1978 IEEE Conf. Decision Contr., San Diego, CA, Jan. 12, 1979, pp. 1326-1367.
14. M. Morf, A. Vieira, and D. T. Lee, “Ladder forms for identification and speech processing,” in Proc. 1977 IEEE Conf. Decision Contr., New Orleans, LA, Dec. 1977, pp. 1074-1078.
15. D. T. L. Lee, M. Morf, and B. Friedlander, “Recursive square-root ladder estimation algorithms,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-29, pp. 627-641, June 1981.
16. E. Satorius and J. Pack, “Application of least squares lattice algorithms to adaptive equalization,” IEEE Trans. Commun., vol. COM-29, pp. 136-142, Feb. 1981.
17. R. S. Medaugh and L. J. Griffiths, “A comparison of two fast linear predictors,” in Proc. 1981 IEEE ICASSP, Atlanta, GA, Apr. 1981.
18. T. L. Lim and M. S. Mueller, “Rapid equalizer start-up using least squares algorithms,” in Proc. 1980 IEEE ICC, Seattle, WA.
19. J. E. Mazo, “On the independence theory of equalizer convergence, “ Bell Syst. Tech. J., vol. 58, pp. 963-993, May-June 1979.