IMPROVEMENT OF THE SIMPLIFIED FTF-TYPE ALGORITHM

Madjid Arezki, Ahmed Benallal, Abderezak Guessoum, Daoud Berkani

2008

Abstract

In this paper, we propose a new algorithm M-SMFTF which reduces the complexity of the simplified FTF-type (SMFTF) algorithm by using a new recursive method to compute the likelihood variable. The computational complexity was reduced from 7L to 6L, where L is the finite impulse response filter length. Furthermore, this computational complexity can be significantly reduced to (2L+4P) when used with a reduced P-size forward predictor. Finally, some simulation results are presented and our algorithm shows an improvement in convergence over the normalized least mean square (NLMS).

References

  1. Arezki, M., Benallal, A., Meyrueis, P., Guessoum A., Berkani, D., 2007. Error Propagation Analysis of Fast Recursive Least Squares Algorithms. Proc. 9th IASTED International Conference on Signal and Image Processing, Honolulu, Hawaii, USA, August 20-22, pp.97-101.
  2. Benallal, A., Gilloire, A., 1988. A New method to stabilize fast RLS algorithms based on a first-order model of the propagation of numerical errors. Proc. ICASSP, New York, USA, pp.1365-1368
  3. Benallal, A., Benkrid, A., 2007. A simplified FTF-type algorithm for adaptive filtering. Signal processing, vol.87, no.5, pp.904-917.
  4. Cioffi, J., Kailath, T., 1984. Fast RLS Transversal Filters for adaptive filtering. IEEE press. On ASSP, vol.32, no.2, pp.304-337.
  5. Gilloire, A., Moulines, E., Slock, D., Duhamel, P., 1996. State of art in echo cancellation. In A.R. Figuers-vidal, Digital Signal processing in telecommunication, Springer, Berlin, pp.45-91
  6. Haykin, S., 2002. Adaptive Filter Theory, Prentice-Hall. NJ, 4th edition.
  7. Macchi, O., 1995. The Least Mean Squares Approach with Applications in Transmission, Wiley. New York.
  8. Mavridis, P.P., Moustakides, G.V., 1996. Simplified Newton-Type Adaptive Estimation Algorithms. IEEE Trans. Signal Process, vol.44, no.8.
  9. Moustakides, G.V., Theodoridis, S., 1999. Fast Newton transversal filters - A new class of adaptive estimation algorithms. IEEE Trans. Signal Process, vol.39, no.10, pp.2184-2193.
  10. Sayed, A.H., 2003. Fundamentals of Adaptive Filtering, John Wiley & Sons. NJ,
  11. Slock, D.T.M., Kailath, T., 1991. Numerically stable fast transversal filters for recursive least squares adaptive filtering,” IEEE transactions on signal processing, vol.39, no.1, pp.92-114.
  12. Slock, D.T.M., 1993. On the convergence behaviour of the LMS and the NLMS algorithms. IEEE Trans. Signal Processing, vol.42, pp.2811-2825.
  13. Treichler, J.R., Johnson, C.R., Larimore, M.G., 2001. Theory and Design of Adaptive Filter, Prentice Hall,
Download


Paper Citation


in Harvard Style

Arezki M., Benallal A., Guessoum A. and Berkani D. (2008). IMPROVEMENT OF THE SIMPLIFIED FTF-TYPE ALGORITHM . In Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008) ISBN 978-989-8111-60-9, pages 156-161. DOI: 10.5220/0001940001560161


in Bibtex Style

@conference{sigmap08,
author={Madjid Arezki and Ahmed Benallal and Abderezak Guessoum and Daoud Berkani},
title={IMPROVEMENT OF THE SIMPLIFIED FTF-TYPE ALGORITHM},
booktitle={Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)},
year={2008},
pages={156-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001940001560161},
isbn={978-989-8111-60-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2008)
TI - IMPROVEMENT OF THE SIMPLIFIED FTF-TYPE ALGORITHM
SN - 978-989-8111-60-9
AU - Arezki M.
AU - Benallal A.
AU - Guessoum A.
AU - Berkani D.
PY - 2008
SP - 156
EP - 161
DO - 10.5220/0001940001560161