A simplified FTF-type algorithm for adaptive filtering

Signal Processing

Volumn 87, Issue 5, 2007, Pages 904-917

  Benallal, Ahmed ^a   Benkrid, Abdelhak ^a  

^a Department of Mechanical Technology   (Saudi Arabia)

Author keywords

Adaptive filters; Convergence speed; Fast Newton transversal filter algorithm; Fast recursive least squares algorithm; Fast transversal filter algorithm; Normalized least mean squares algorithm; Numerical stability; Prediction; Tracking capability

Indexed keywords

ADAPTIVE ALGORITHMS; COMPUTATIONAL COMPLEXITY; CONVERGENCE OF NUMERICAL METHODS; LEAST SQUARES APPROXIMATIONS; ROBUSTNESS (CONTROL SYSTEMS);

FAST NEWTON TRANSVERSAL FILTER ALGORITHMS; FAST RECURSIVE LEAST SQUARES ALGORITHM; FAST TRANSVERSAL FILTER ALGORITHMS; NORMALIZED LEAST MEAN SQUARES ALGORITHMS; TRACKING CAPABILITY;

ADAPTIVE FILTERING;

EID: 33846638840     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2006.08.013     Document Type: Article

References (18)

1. Haykin S. Adaptive Filter Theory. fourth ed. (2002), Prentice-Hall, Englewood Cliffs, NJ
2. Belanger M. Adaptive Digital Filters and Signal Analysis (1987), Marcel Dekker, New York
3. Caryannis G., Manolakis D., and Kalouptsidis N. A fast sequential algorithm for least squares filtering and prediction. IEEE Trans. Acoust. Speech Signal Process. ASSP-31 (December 1983) 1394-1402
4. Cioffi J., and Kailath T. Fast recursive least squares transversal filters for adaptive filtering. IEEE Trans. Acoust. Speech Signal Process. ASSP-32 (April 1984) 304-337
5. Moustakides G., and Theodoridis S. Fast Newton transversal filters- A new class of adaptive estimation algorithms. IEEE Trans. Signal Process. 39 10 (1991) 2184-2193
6. Petition T., Gilloire A., and Theodoridis S. The fast Newton transversal filter: an efficient scheme for acoustic echo cancellation in mobile radio. IEEE Trans. Signal Process. 42 (March 1993) 509-518
7. Mavridis P.P., and Moustakides G.V. Simplified Newton-Type Adaptive Estimation Algorithms. IEEE Trans. Signal Process. 44 (August 1996) 8
8. A. Benallal, A. Gilloire, A New method to stabilize fast RLS algorithms based on a first-order model of the propagation of numerical errors, Proc. Of ICASSP88, New York, 1988.
9. D.T.M. Slock, T. Kailath, Numerically stable fast transversal filters for recursive least squares adaptive filtering, IEEE Trans. Signal Process. 39(1) (Januray 1991).
10. Benallal A., and Gilloire A. Instabilite et stabilite numerique des algorithmes de moindres carrees rapides excites par la parole. XII ieme Colloque GRESTI, Juan les Pins (June 1989) 509-512
11. Macchi O. Adaptive Processing: the LMS approche with applications to transmission (1995), Wiley, New York
12. Slock D.T.M. On the convergence behaviour of the LMS and the normalized LMS algorithms. IEEE Trans. Signal Process. 42 (March 1993) 2811-2825
13. Gilloire A., Moulines E., Slock D., and Duhamel P. State of art in echo cancellation. In: Figuers-vidal A.R. (Ed). Digital Signal processing in telecommunication (1996), Springer, Berlin 45-91
14. Arezki M., Benallal A., Guessoum A., and Berkani D. Three New Versions of Numerically Stable Fast Least Squares Algorithms (NS-FRLS) for Adaptive Filtering, CSNDSP04 Fourth International Symposium (July 2004), Newcastle, United Kingdom
15. S. Blinde, A numerically stable FTF with leakage correction, IEEE Process. Lett. 2(6) (June 1995).
16. K. Ozeki, T. Umeda, An Adaptive Filtering Algorithm Using an Orthogonal Projection to an Affine Subspace and Its Properties, Electron. Commun. Jpn. 67-A(5) (1984).
17. Gay S.L., and Tavathia S. The Fast Affine Projection Algorithm, Proc. of Int. Conf. on Acoustics. Speech Signal Process. 666 (1995) 3023-3026
18. Regalia P.A. Numerical stability issues in fast least-squares adaptation algorithms. Opt. Eng. 31 (June 1992) 1144-1152