On the Signal Power Normalization Approach to the Escalator Adaptive filter Algorithms

  • Kim Nam-Yong (Samcheok National University, Dept. of Comm. & Inform.)
  • 발행 : 2006.08.01

초록

A normalization approach to coefficient adaptation in the escalator(ESC) filter structure that conventionally employs least mean square(LMS) algorithm is introduced. Using Taylor's expansion of the local error signal, a normalized form of the ESC-LMS algorithm is derived. Compared with the computational complexity of the conventional ESC-LMS algorithm employs input power estimation for time-varying convergence coefficient using a single-pole low-pass filter, the computational complexity of the proposed method can be reduced by 50% without performance degradation.

키워드

참고문헌

  1. B. Widrow et al., 'Stationary and nonstationary learning characteristics of the LMS adaptive filter,' Proc. IEEE, Vol.64, pp.1151-1162, Aug. 1976 https://doi.org/10.1109/PROC.1976.10286
  2. N. Ahmed and D. H. Youn, 'On realization and related algorithm for adaptive prediction.' IEEE Trans. Acoust., Speech, Signal Processing, Vol. ASSP-28, pp.493-497, Oct. 1980
  3. K. M. Kim, I. W. Cha and D. H. Youn, 'Adaptive Multichannel Digital Filter with Lattice-Escalator Hybrid Structure,' Proceedings of the 1990 ICASSP, New Mexico, USA, Vol. 3, pp.1413-1416, April. 1990
  4. V. N. Parikh and A. Z. Baraniecki, 'The Use of the Modified Escalator Algorithm to Improve the Performance of Transform-Domain LMS Adaptive Filters.' IEEE Trans. on Signal Processing, Vol.46, No.3, pp.625-635, March, 1998 https://doi.org/10.1109/78.661330
  5. E. Soria-Olivias, J. Calpe-Maravilla, J. F.GuerroMartinez, M. Martinez-Sober, and J. Espi-Lopez, 'An easy demonstration of the optimum value of the adaptation constant in the LMS algorithm', IEEE Trans. Education, Vol.41, p.81, 1998 https://doi.org/10.1109/13.660794
  6. S. Haykin, 'Adaptive filter theory', Prentice-Hall, Third Edn., 1996