Skip to main content
Log in

Sard-optimal prefilters for the Fast Wavelet Transform

  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

A direct input of function samples into the Fast Wavelet Transform often gives inaccurate results. We use the refinement equation for the construction of prefiltering quadrature formulas which are optimal in Sard's sense, i.e.,in the standard class of functions with ‖ f (p)2 < ∞. A detailed analysis of the error and several applications are given.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. G. Beylkin, On the representation of operators in bases ofcompactly supported wavelets, SIAM J. Numer. Anal. 6 (1992) 1716–1740.

    Article  MATH  MathSciNet  Google Scholar 

  2. G. Beylkin, R. Coifman and V. Rokhlin, Fast Wavelet Transformand numerical algorithms I, Comm. Pure Appl. Math. 44 (1991) 141–183.

    MATH  MathSciNet  Google Scholar 

  3. H. Brass, Quadraturverfahren (Vandenhoeck und Ruprecht, Göttingen, 1977).

    Google Scholar 

  4. H. Brass, On the quality of algorithmsbased on spline interpolation, Numer. Algorithms 13 (1996) 159–177.

    Article  MATH  MathSciNet  Google Scholar 

  5. H. Brass and K.-J. Förster, On the application of the Peanorepresentation of linear functionals in numerical analysis, Preprint (1996).

  6. W. Dahmen and C. Micchelli, Using the refinement equation for evaluating integrals of wavelets, SIAM J. Numer. Anal. 30 (1993) 507–537.

    Article  MATH  MathSciNet  Google Scholar 

  7. I. Daubechies, Ten Lectures on Wavelets, CBMS-NSF RegionalConference Series in Applied Mathematics 61 (SIAM, Philadelphia, PA, 1992).

    Google Scholar 

  8. S. Ehrich, Pointwise error bounds for orthogonal cardinal splineapproximation, submitted (presently available as Hildesheimer Informatik-Berichte 30/96 or from http://www.informatik.uni-hildesheim.de/~ehrich).

  9. W. Gawronski and U. Stadtmüller, On the zeros of Lerch's transcendental function with real parameters, J. Approx. Theory 53 (1988) 354–364.

    Article  MATH  Google Scholar 

  10. A. Sard, Linear Approximation, Mathematical Surveys 9(Amer. Math. Society, Providence, RI, 1963).

    Google Scholar 

  11. I.J. Schoenberg,Monosplines and quadrature formulae, in: Theory and Application of Spline Functions, ed. T.N.E. Greville (Academic Press, New York, 1969) pp. 157–207.

    Google Scholar 

  12. I.J. Schoenberg, Cardinal Spline Interpolation, CBMS-NSF Regional Conference Series in Applied Mathematics 12 (SIAM, Philadelphia, PA, 1973).

    Google Scholar 

  13. L. Schumaker, Spline Functions: BasicTheory (Wiley Interscience, 1981).

  14. G. Strang and T. Nguyen,Wavelets and Filter Banks (Wellesley-Cambridge Press, Wellesley, MA, 1996).

    Google Scholar 

  15. W. Sweldens and R. Piessens, Quadrature formulae andasymptotic error expansions for wavelet approximations of smooth functions, SIAM J. Numer. Anal. 31 (1994) 1240–1264.

    Article  MATH  MathSciNet  Google Scholar 

  16. S. Wolfram,Mathematica - A System for Doing Mathematics by Computer (Addison Wesley, 2nd ed., 1991).

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ehrich, S. Sard-optimal prefilters for the Fast Wavelet Transform. Numerical Algorithms 16, 303–319 (1997). https://doi.org/10.1023/A:1019103617219

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1019103617219

Navigation