Wavelets and Statistics pp 55-81

Part of the Lecture Notes in Statistics book series (LNS, volume 103) | Cite as

WaveLab and Reproducible Research

  • Jonathan B. Buckheit
  • David L. Donoho

Abstract

Wavelab is a library of wavelet-packet analysis, cosine-packet analysis and matching pursuit. The library is available free of charge over the Internet. Versions are provided for Macintosh, UNIX and Windows machines.

Wavelab makes available, in one package, all the code to reproduce all the figures in our published wavelet articles. The interested reader can inspect the source code to see exactly what algorithms were used, how parameters were set in producing our figures, and can then modify the source to produce variations on our results. WAVELAB has been developed, in part, because of exhortations by Jon Claerbout of Stanford that computational scientists should engage in “really reproducible” research.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Antonini, M., Barlaud, M., Mathieu, P. and Daubechies, I. (1991). Image coding using wavelet transforms. To appear,IEEE Proc. Acoustics, Speech and Signal Processing.Google Scholar
  2. [2]
    Buckheit, J.B. and Donoho, D.L. (1995). A Cartoon Guide to Wavelets. Technical Report, Department of Statistics, Stanford University.ftp://playfair.Stanford.edu/pub/buckheit/toons.ps.Google Scholar
  3. [3]
    Buckheit, J.B, Chen, S., Donoho, D.L., Johnstone, I.M. and Scargle, J.D. (1995). About WaveLab,ftp://playfair.Stanford.edu/pub/wavelab/AboutWaveLab.ps.Google Scholar
  4. [4]
    Buckheit, J.B., Donoho, D.L. and Scargle, J.D.WaveLab Architecture. ftp://playfair.Stanford.edu/pub/wavelab/WaveLabArch.ps.Google Scholar
  5. [5]
    Buckheit, J.B, Chen, S., Donoho, D.L., Johnstone, I.M. and Scargle, J.D. (1995).WaveLab Reference Manual.ftp://playfair.stanford.edu/pub/wavelab/WaveLabRef.ps.Google Scholar
  6. [6]
    Chen, S. and Donoho, D.L. (1994). On Basis Pursuit. Technical Report, Department of Statistics, Stanford University.ftp://playfair.stanford.edU/pub/chen_s/asilomar.ps.Z.Google Scholar
  7. [7]
    Claerbout, Jon (1994). Hypertext Documents about Reproducible Research,http://sepwww.Stanford.edu.Google Scholar
  8. [8]
    Cohen, A., Daubechies, I. and Feauveau, J.C. (1992). Biorthogonal bases of compactly supported wavelets.Comm. Pure Appl. Math. 45485–560.MathSciNetMATHCrossRefGoogle Scholar
  9. [9]
    Cohen, A., Daubechies, I., Jawerth, B. and Vial, P. (1992). Multiresolution analysis, wavelets, and fast algorithms on an interval.Comptes Rendus Acad. Sci. Paris A 316417–421.MathSciNetGoogle Scholar
  10. [10]
    Coifman, R.R. and Donoho, D.L. (1995). Translation-Invariant De-Noising.This Volume.Google Scholar
  11. [11]
    Coifman, R.R. and Meyer, Y. (1991). Remarques sur l’analyse de Fourier à fenêtreComptes Rendus Acad. Sci. Paris(A)312259–261.MathSciNetMATHGoogle Scholar
  12. [12]
    Coifman, R.R., Meyer, Y. and Wickerhauser, M.V. (1992). Wavelet analysis and signal processing. InWavelets and Their Applications, pp. 153–178, M.B. Ruskai et al., eds., Jones and Bartlett, Boston.Google Scholar
  13. [13]
    Coifman, R.R. and Wickerhauser, M.V. (1992). Entropy-based algorithms for best-basis selection.IEEE Trans. Info. Theory 38(2)713–718.MATHCrossRefGoogle Scholar
  14. [14]
    Daubechies, I. (1992)Ten Lectures on Wavelets. SIAM, Philadelphia.MATHGoogle Scholar
  15. [15]
    DeVore, R.A., Jawerth, B. and Lucier, B.J. (1992). Image compression through wavelet transform coding.IEEE Trans. Info Theory,38(2)719–746.MathSciNetMATHCrossRefGoogle Scholar
  16. [16]
    Donoho, D.L. (1992). Interpolating Wavelet Transforms. Technical Report, Department of Statistics, Stanford University.ftp://playfair.Stanford.edu/pub/donoho/interpol.ps.Z.Google Scholar
  17. [17]
    Donoho, D.L. (1993) Nonlinear Wavelet Methods for Recovery of Signals, Images, and Densities from Noisy and Incomplete Data. InDifferent Perspectives on Wavelets, I. Daubechies, ed. American Mathematical Society, Providence, RI.ftp://playfair.Stanford.edu/pub/donoho/ShortCourse.ps.Z.Google Scholar
  18. [18]
    Donoho, D.L. (1994). On Minimum Entropy Segmentation. InWavelets: Theory, Algorithms and Applications. C.K. Chui, L. Montefusco and L. Puccio, eds. Academic Press, San Diego,ftp://playfair.Stanford.edu/pub/donoho/MES_TechReport.ps.Z.Google Scholar
  19. [19]
    Donoho, D.L. (1993). Smooth Wavelet Decompositions with Blocky Coefficient Kernels. InRecent Advances in Wavelet Analysis, L. Schumaker and F. Ward, eds. Academic Press,ftp://playfair.Stanford.edu/pub/donoho/blocky.ps.Z.Google Scholar
  20. [20]
    Donoho, D.L. (1993). Unconditional Bases are Optimal Bases for Data Compression and for Statistical Estimation.Applied and Computational Harmonic Analysis,1, 100–115.ftp://playfair.Stanford.edu/pub/donoho/UBRelease.ps.Z.MathSciNetMATHCrossRefGoogle Scholar
  21. [21]
    Donoho, D.L. (1993). Wavelet Shrinkage and W.V.D. — A Ten-Minute Tour. InProgress in Wavelet Analysis and Applications, Y. Meyer and S. Roques, eds. Éditions Frontières, Gif-sur-Yvette.ftp://playfair.Stanford,edu/pub/donoho/toulouse.ps.Z.Google Scholar
  22. [22]
    Donoho, D.L. and Johnstone, I.M. (1994). Adapting to Unknown Smoothness by Wavelet Shrinkage To appear,J. Amer. Stat Assoc. ftp://playfair.Stanford.edu/pub/donoho/ausws.ps.Z.Google Scholar
  23. [23]
    Donoho, D.L. and Johnstone, I.M. (1994). Ideal Spatial Adaptation via Wavelet Shrinkage.Biometrika,,81, 425–455.ftp://playfair.stanford.edU/pub/donoho/isaws.ps.Z.MathSciNetMATHCrossRefGoogle Scholar
  24. [24]
    Donoho, D.L. and Johnstone, I.M. (1994). Ideal Time-Frequency Denoising. Technical Report, Department of Statistics, Stanford University.ftp://playfair.Stanford.edu/pub/donoho/tfdenoise.ps.Z.Google Scholar
  25. [25]
    Donoho, D.L., Johnstone, I.M., Kerkyacharian, G. and Picard, D. (1993). Wavelet Shrinkage: Asymptopia.J. Roy. Statist Soc. B.2, 301–369.ftp://playfair.Stanford.edu/pub/donoho/asymp.ps.Z.Google Scholar
  26. [26]
    Kolaczyk, E. (1994). WVD Solution of Inverse Problems. Ph.D. Thesis, Stanford University.Google Scholar
  27. [27]
    Mallat, S. and Zhang, S. (1993). Matching Pursuits with Time-Frequency Dictionaries.IEEE Transactions on Signal Processing,41(12): 3397–3415.MATHCrossRefGoogle Scholar
  28. [28]
    Meyer, Y.Wavelets:Algorithms and Applications. SIAM: Philadelphia, 1993.MATHGoogle Scholar
  29. [29]
    Wickerhauser, M.V. (1994).Adapted Wavelet Analysis, from Theory to Software. AK Peters: Boston.MATHGoogle Scholar

Copyright information

© Springer-Verlag New York 1995

Authors and Affiliations

  • Jonathan B. Buckheit
    • 1
  • David L. Donoho
    • 1
  1. 1.Stanford UniversityStanfordUSA

Personalised recommendations