Systolic Algorithms for Adaptive Signal Processing

  • Marc Moonen
Conference paper
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 69)

Abstract

An overview is given of recent work in parallel algorithms development. It is shown how one specific type of systolic algorithm/array can be used for several ‘classical’ adaptive signal processing tasks, such as recursive least squares parameter estimation, SVD updating, Kalman filtering, beamforming and direction finding, etc.

Keywords

Covariance Propa sinO 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    D. B. Duncan, S.D. Horn, Linear dynamic recursive estimation from the viewpoint of regression analysis, J. Amer. Statist. Assoc. 67 (1972), 815–821.MathSciNetMATHCrossRefGoogle Scholar
  2. [2]
    F. Gaston, G. Irwin, Systolic kalman filtering: an overview, IEE Proceedings 137 (4) (1990), 235–244.MATHGoogle Scholar
  3. [3]
    W.M. Gentleman, H.T. Kung, Matrix triangularization by systolic arrays. Real-Time Signal Processing IV, Proc. SPIE 298 (1982), 19–26.Google Scholar
  4. [4]
    S.Y. Kung, VLSI array processors, Englewood Cliffs, NJ., Prentice Hall 1988.Google Scholar
  5. [5]
    F.T. Luk, A triangular processor array for computing singular values. Lin. Alg. Appl. 77 (1986), 259–273.MATHCrossRefGoogle Scholar
  6. [6]
    M. Moonen, P. Van Dooren, J. Vandewalle, An SVD updating algorithm forsubspace tracking, Internal Report K.U. Leuven, ESAT/SISTA 1989-13. (to appear in) SIAM J. Matrix Anal. Appl. 13 (4) (1992).CrossRefGoogle Scholar
  7. [7]
    M. Moonen, P. Van Dooren, J. Vandewalle, A systolic array for SVD updating, Internal Report K.U. Leuven, ESAT/SISTA 1990-18. (to appear in) SIAM J. Matrix Anal. Appl. (1993).Google Scholar
  8. [8]
    M. Moonen, P. Van Dooren, J. Vandewalle, A systolic algorithm for QSVD updating. Signal Processing 25 (2) (1991), 203–213.MATHCrossRefGoogle Scholar
  9. [9]
    M. Moonen, J. Vandewalle, Recursive least squares with stabilized inverse factorization, Signal Processing 21 (1) (1990), 1–15.MathSciNetMATHCrossRefGoogle Scholar
  10. [10]
    M. Moonen, J. Vandewalle, A systolic array for recursive least squares computations, Internal Report K.U. Leuven, ESAT/SISTA 1990-22. (to appear in) IEEE Trans. Signal Processing, 1993.Google Scholar
  11. [11]
    M. Moonen, J. Vandewalle, A square root covariance algorithm for constrained recursive least squares estimation, Journal of VLSI Signal Processing 3 (3) (1991), 163–172.MATHCrossRefGoogle Scholar
  12. [12]
    M. Moonen, Implementing the square-root information Kalman filter on a Jacobi-type systolic array. Internal Report K.U. Leuven, ESAT/SISTA 1991-30. (to appear in) Journal of VLSI Signal Processing.Google Scholar
  13. [13]
    M. Moonen, F. Van Poucke, E. Deprettere, Parallel and adaptive high resolution direction finding. Internal Report K.U. Leuven, ESAT/SISTA 1992-32. (submitted for publication).Google Scholar
  14. [14]
    C.C. Paige, M. Saunders, Least squares estimation of discrete linear dynamic systems using orthogonal transformations, SIAM J. Numer. Anal. 14 (2) (1977), 180–193.MathSciNetMATHCrossRefGoogle Scholar
  15. [15]
    C.T. Pan, R.J. Plemmons, Least squares modifications with inverse factorization: parallel implications, Journal of Computational and Applied Mathematics 27 (1–2) (1989), 109–127.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag New York, Inc. 1995

Authors and Affiliations

  • Marc Moonen
    • 1
  1. 1.ESAT-KULHeverleeBelgium

Personalised recommendations