A robust, parallelizable, O(m), a posteriori recursive least squares algorithm for efficient adaptive filtering

@article{Papaodysseus1999ARP,
  title={A robust, parallelizable, O(m), a posteriori recursive least squares algorithm for efficient adaptive filtering},
  author={Constantin Papaodysseus},
  journal={IEEE Trans. Signal Processing},
  year={1999},
  volume={47},
  pages={2552-2558}
}
This correspondence presents a new recursive least squares (RLS) adaptive algorithm. The proposed computational scheme uses a finite window by means of a lemma for the system matrix inversion that is, for the first time, stated and proven here. The new algorithm has excellent tracking capabilities. Moreover, its particular structure allows for stabilization by means of a quite simple method. Its stabilized version performs very well not only for a white noise input but also for nonstationary… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Fast calculations of gain matrices for recursive estimation schemes

  • L. Ljung, M. Morf, D. Falconer
  • Int. J. Contr., vol. 27, pp. 1–19, Jan. 1988.
  • 1988
1 Excerpt

Efficient time-recursive leastsquares algorithms for finite-memory adaptive filtering

  • D. Manolakis, F. Ling, L. Proakis
  • IEEE Trans. Circuits Syst. , vol. CAS-34, Apr…
  • 1987
3 Excerpts

A fast sequential algorithm for least-squares filtering and prediction

  • G. Carayannis, D. Manolakis, N. Kalouptsidis
  • IEEE Trans. Acoust., Speech, Signal Processing…
  • 1983
2 Excerpts

Similar Papers

Loading similar papers…