Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-07T23:24:00.678Z Has data issue: false hasContentIssue false

Wavelets*

Published online by Cambridge University Press:  07 November 2008

Ronald A. DeVore
Affiliation:
Department of MathematicsUniversity of South Carolina, Columbia, SC 29208USA, E-mail: [email protected]
Bradley J. Lucier
Affiliation:
Department of MathematicsPurdue University, West Lafayette, IN 47907USA, E-mail: [email protected]

Extract

The subject of ‘wavelets’ is expanding at such a tremendous rate that it is impossible to give, within these few pages, a complete introduction to all aspects of its theory. We hope, however, to allow the reader to become sufficiently acquainted with the subject to understand, in part, the enthusiasm of its proponents toward its potential application to various numerical problems. Furthermore, we hope that our exposition can guide the reader who wishes to make more serious excursions into the subject. Our viewpoint is biased by our experience in approximation theory and data compression; we warn the reader that there are other viewpoints that are either not represented here or discussed only briefly. For example, orthogonal wavelets were developed primarily in the context of signal processing, an application upon which we touch only indirectly. However, there are several good expositions (e.g. Daubechies (1990) and Rioul and Vetterli (1991)) of this application. A discussion of wavelet decompositions in the context of Littlewood-Paley theory can be found in the monograph of Frazier et al. (1991). We shall also not attempt to give a complete discussion of the history of wavelets. Historical accounts can be found in the book of Meyer (1990) and the introduction of the article of Daubechies (1990). We shall try to give sufficient historical commentary in the course of our presentation to provide some feeling for the subject's development.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Battle, G. (1987), ‘A block spin construction of ondelettes, Part I: Lemarié functions’, Comm. Math. Phys. 110, 601615.CrossRefGoogle Scholar
Ben Artzi, A. and Ron, A. (1990), ‘On the integer translates of a compactly supported function: Dual bases and linear projectors’, SIAM J. Math. Anal. 21, 15501562.Google Scholar
Beylkin, G., Coifman, R. and Rokhlin, V. (1991), ‘Fast wavelet transforms and numerical algorithms I’, Comm. Pure Appl. Math. XLIV, 141183.Google Scholar
de Boor, C., DeVore, R. and Ron, A. (1991a), ‘Approximation from shift invariant spaces’, Preprint.Google Scholar
de Boor, C., DeVore, R. and Ron, A. (1991b), ‘Wavelets and pre-wavelets’, Preprint.Google Scholar
de Boor, C., DeVore, R. and Ron, A. (1991c), ‘The structure of finitely generated shift invariant spaces in L 2(ℝd)’, Preprint.CrossRefGoogle Scholar
de Boor, C. and Ron, A. (1991), ‘Fourier analysis of approximation orders from principal shift invariant spaces’, Constructive Approx., to appear.Google Scholar
Cavaretta, A., Dahmen, W. and Micchelli, C. (1991), ‘Subdivision for computer aided geometric design’, Memoirs Amer. Math. Soc. 93.Google Scholar
Chui, C. K., Stöckler, J. and Ward, J. D. (1991), ‘Compactly supported box-spline wavelets’, CAT Report, Texas A&M University 230Google Scholar
Chui, C. K. and Wang, J. Z. (1990), ‘A general framework for compactly supported splines and wavelets’, CAT Report, Texas A&M University 219.Google Scholar
Chui, C. K. and Wang, J. Z. (1991), ‘On compactly supported spline wavelets and a duality principle’, Trans. Amer. Math. Soc., to appear.Google Scholar
Dahmen, W. and Micchelli, C. (1990), ‘On stationary subdivision and the construction of compactly supported wavelets’, Multivariate Approximation and Interpolation Vol. 94 (Haussmann, W. and Jetter, K., eds) ISNM, Birkhauser Verlag (Boston) pp. 6989.CrossRefGoogle Scholar
Daubechies, I. (1988), ‘Orthonormal bases of compactly supported wavelets’, Comm. Pure Appl. Math. XLI, 909996.CrossRefGoogle Scholar
Daubechies, I. (1990), ‘The wavelet transform, time-frequency localization and signal analysis’, IEEE Trans. Information Theory 36, 9611005.Google Scholar
DeVore, R., Jawerth, B. and Lucier, B. (1991a), ‘Data compression using wavelets: Error, smoothness, and quantization’, DCC-91, Data Compression Conference (Storer, A. and Reif, J. H., eds), IEEE Computer Society Press (Los Alamitos, CA) pp. 186195.Google Scholar
DeVore, R., Jawerth, B. and Lucier, B. (1991b), ‘Surface compression’, Computer Aided Geometric Design, to appear.Google Scholar
DeVore, R., Jawerth, B., and Lucier, B. (1991c), ‘Image compression through wavelet transform coding’, IEEE Trans. Information Theory to appear.Google Scholar
DeVore, R., Jawerth, B. and Popov, V. (1991d), ‘Compression of wavelet decompositions’, Amer. J. Math., to appear.Google Scholar
DeVore, R. and Lorentz, G. (1992), Constructive Approximation Springer Grundlehren (Heidelberg).Google Scholar
DeVore, R. and Lucier, B. (1989), ‘High order regularity for solutions of the inviscid Burgers equation’, Nonlinear Hyperbolic Problems (Proc. Advanced Research Workshop, Bordeaux, France, June 1988, Springer Lecture Notes in Mathematics, 1402) (Carasso, C., Charrier, P., Hanouzet, B. and Joly, J.-L., eds) Springer-Verlag (New York) pp. 147154.CrossRefGoogle Scholar
DeVore, R. and Lucier, B. (1990), ‘High order regularity for conservation laws’, Indiana Univ. Math. J. 39, 413430.CrossRefGoogle Scholar
DeVore, R. and Popov, V. (1988), ‘Interpolation spaces and non-linear approximation’, Function Spaces and Applications (Springer Lecture Notes in Mathematics, 1302) (Cwikel, M., Peetre, J., Sagher, Y. and Wallin, H., eds) Springer (New York) pp. 191205.CrossRefGoogle Scholar
Eirola, T. (1992) ‘Sobolev characterization of solutions of dilation equations’, SIAM J. Math. Anal, to appear.CrossRefGoogle Scholar
Frazier, M. and Jawerth, B. (1990), ‘A discrete transform and decompositions of distribution spaces’, J. Funct. Anal. 93, 34170.CrossRefGoogle Scholar
Frazier, M., Jawerth, B. and Weiss, G. (1991), Littlewood–Paley Theory and the Study of Function Spaces Conference Board of the Mathematical Sciences, Regional Conference Series in Mathematics, Number 79, Amer. Math. Soc. (Providence, RI)CrossRefGoogle Scholar
Jaffard, S. (1991) ‘Wavelet methods for fast resolution of elliptic problems’, PreprintGoogle Scholar
Jaffard, S. and Meyer, Y. (1989), ‘Bases ondelettes dans des ouverts de ℝn’, J. Math. Pures Appl. 68, 95108.Google Scholar
Jia, R-Q. and Micchelli, C. (1991), ‘Using the refinement equation for the construction of pre-wavelets II: power of two’, Curves and Surfaces, (Laurent, P. J., LeMéhauté, A., and Schumaker, L., eds) Academic Press (New York) pp. 209246.CrossRefGoogle Scholar
Karlin, S. and Studden, W. (1966), Tchebycheff Systems with Application to Analysis and Statistics Wiley Interscience (New York).Google Scholar
Lorentz, R. A. H. and Madych, W. R. (1991) Wavelets and generalized box splines, preprint.Google Scholar
Mallat, S. G. (1989), ‘Multi-resolution approximations and wavelet orthonormal bases of L 2(ℝ)’, Trans. Amer. Math. Soc. 315, 6987.Google Scholar
Meyer, Y. (1987), ‘Wavelets with compact support’, Zygmund Lectures (University of Chicago).Google Scholar
Meyer, Y. (1990), Ondelettes et Opérateurs I: Ondelettes Hermann (Paris).Google Scholar
Micchelli, C. (1991), ‘Using the refinement equation for the construction of pre-wavelets’, Numer. Alg. 1, 75116.CrossRefGoogle Scholar
Oswald, P. (1991) ‘On discrete norm estimates related to multi-level preconditioners in the finite elment method’, Preprint.Google Scholar
Riemenschneider, S. D. and Shen, Z. W. (1991), ‘Box splines, cardinal splines, and wavelets’, Approximation Theory and Functional Analysis (Chui, C. K., ed.) Academic Press (New York) pp. 133149.Google Scholar
Riemenschneider, S. D. and Shen, Z. W. (1992) ‘Wavelets and pre-wavelets in low dimensions’, J. Approx. Theory to appear.Google Scholar
Rioul, O. and Vetterli, M. (1991), ‘Wavelets and signal processing’, IEEE Signal Processing Magazine 8, (4) 1438.CrossRefGoogle Scholar
Schoenberg, I. (1946), ‘Contributions to the problem of approximation of equidistant data by analytic functions, Parts A & B’, Quart. Appl. Math. IV, 4599, 112–141.Google Scholar
Schoenberg, I. (1973), Cardinal Spline Interpolation (Regional Conference Series in Applied Mathematics 12) SIAM (Philadelphia).CrossRefGoogle Scholar
Strang, G. and Fix, G. (1973), ‘A Fourier analysis of the finite element variational method’, C.I.M.E. II Ciclo 1971, Constructive Aspects of Functional Analysis (Geymonat, G., ed.) pp. 793840.Google Scholar
Strömberg, J. O. (1981) ‘A modified Franklin system and higher-order spline systems on ℝn as unconditional basis for Hardy spaces’, Conference in Harmonic Analysis in Honor of Antoni Zygmund Vol II (Beckner, W. et al. , eds) Wadsworth pp. 475493.Google Scholar