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Wavelets andWavelet Based Numerical Homogenization

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 66))

Wavelets is a tool for describing functions on different scales or level of detail. In mathematical terms, wavelets are functions that form a basis for \(L^2 \left(\mathbb{R}\right)\) with special properties; the basis functions are spatially localized and correspond to different scale levels. Finding the representation of a function in this basis amounts to making a multiresolution decomposition of the function. Such a wavelet representation lends itself naturally to analyzing the fine and coarse scales as well as the localization properties of a function.Wavelets have been used in many applications, from image and signal analysis to numerical methods for partial differential equations (PDEs). In this tutorial we first go through the basic wavelet theory and then show a more specific application where wavelets are used for numerical homogenization.We will mostly give references to the original sources of ideas presented. There are also a large number of books and review articles that cover the topic of wavelets, where the interested reader can find further information, e.g. [25, 51, 48, 7, 39, 26, 23], just to mention a few.

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References

  1. B. Alpert. A class of bases in L 2 for the sparse representation of integral operators. SIAM J. Math. Anal., 24(1):246–262, 1993.

    Article  MATH  MathSciNet  Google Scholar 

  2. J. Anderson. Computational Fluid Dynamics, The Basics with Applications. McGraw-Hill, 1995.

    Google Scholar 

  3. U. Andersson, B. Engquist, G. Ledfelt, and O. Runborg. A contribution to wavelet-based subgrid modeling. Appl. Comput. Harmon. Anal., 7:151–164, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  4. O. Axelsson. Iterative Solution Methods. Cambridge University Press, 1994.

    Google Scholar 

  5. G. Battle. A block spin construction of ondelettes. Comm. Math. Phys., 110:601–615, 1987.

    Article  MathSciNet  Google Scholar 

  6. A. Bensoussan, J.-L. Lions, and G. Papanicolau. Asymptotic Analysis for Periodic Structures. North-Holland Publ. Comp., The Netherlands, 1978.

    MATH  Google Scholar 

  7. J. Bergh, F. Ekstedt, and M. Lindberg. Wavelets. Studentlitteratur, Lund, 1999.

    Google Scholar 

  8. G. Beylkin and M. Brewster. A multiresolution strategy for numerical homogenization. Appl. Comput. Harmon. Anal., 2:327–349, 1995.

    Article  MATH  MathSciNet  Google Scholar 

  9. G. Beylkin, M. E. Brewster, and A. C. Gilbert. A multiresolution strategy for numerical homogenization of nonlinear ODEs. Appl. Comput. Harmon. Anal., 5:450–486, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  10. G. Beylkin, R. Coifman, and V. Rokhlin. Fast wavelet transforms and numerical algorithms I. Comm. Pure Appl. Math., 44:141–183, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  11. G. Beylkin and N. Coult. A multiresolution strategy for reduction of elliptic PDEs and eigenvalue problems. Appl. Comput. Harmon. Anal., 5:129–155, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  12. E. J. Candès and D. L. Donoho. Ridgelets: the key to higher-dimensional intermittency? Phil. Trans. R. Soc. Lond. A., 357:2495–2509, 1999.

    Article  MATH  Google Scholar 

  13. E. J. Candès and D. L. Donoho. Curvelets — a surprisingly effective nonadaptive representation for objects with edges. In A. Cohen, C. Rabut, and L. L. Schumaker, editors, Curves and Surfaces, pages 105–120. Vanderbilt Univ. Press, 2000.

    Google Scholar 

  14. T. Chan and T. Mathew. The interface probing technique in domain decomposition. SIAM J. Matrix Anal. Appl., 13(1):212–238, January 1992.

    Article  MATH  MathSciNet  Google Scholar 

  15. A. Chertock and D. Levy. On wavelet-based numerical homogenization. Multiscale Model. Simul., 3(1):65–88 (electronic), 2004/05.

    Article  MathSciNet  Google Scholar 

  16. C. K. Chui and J. Z. Wang. A cardinal spline approach to wavelets. Proc. Amer. Math. Soc., 113:785–793, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  17. A. Cohen, W. Dahmen, and R. A. DeVore. Adaptive wavelet methods for elliptic operator equations: Convergence rates. Math. Comp., 70:27–75, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  18. A. Cohen, I. Daubechies, and J. Feauveau. Bi-orthogonal bases of compactly supported wavelets. Comm. Pure Appl. Math., 45:485–560, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  19. A. Cohen, I. Daubechies, B. Jawerth, and P. Vial. Multiresolution analysis, wavelets and fast algorithms on an interval. C. R. Acad. Sci. Paris Sé r. I Math., I(316):417–421, 1993.

    MathSciNet  Google Scholar 

  20. A. Cohen, S. M. Kaber, S. Mü ller, and M. Postel. Fully adaptive multiresolution finite volume schemes for conservation laws. Math. Comp., 72(241):183–225, 2003.

    Article  MATH  MathSciNet  Google Scholar 

  21. R. R. Coifman, Y. Meyer, S. Quake, and M. V. Wickerhauser. Signal processing and compression with wave packets. In Y. Meyer, editor, Proceedings of the International Conference on Wavelets, Marseille, 1989. Masson, Paris, 1992.

    Google Scholar 

  22. C. Concus, G. H. Golub, and G. Meurant. Block preconditioning for the conjugate gradient method. SIAM J. Sci. Stat. Comp., 6:220–252, 1985.

    Article  MATH  MathSciNet  Google Scholar 

  23. W. Dahmen. Wavelet and multiscale methods for operator equations. Acta Numerica, 6:55–228, 1997.

    Article  MathSciNet  Google Scholar 

  24. I. Daubechies. Orthonormal bases of compactly supported wavelets. Comm. Pure Appl. Math., 41:909–996, 1988.

    Article  MATH  MathSciNet  Google Scholar 

  25. I. Daubechies. Ten Lectures on Wavelets. SIAM, 1991.

    Google Scholar 

  26. R. A. DeVore and B. J. Lucier. Wavelets. Acta Numerica, 1:1–56, 1991.

    Article  MathSciNet  Google Scholar 

  27. M. Dorobantu and B. Engquist. Wavelet-based numerical homogenization. SIAM J. Numer. Anal., 35(2):540–559, April 1998.

    Article  MATH  MathSciNet  Google Scholar 

  28. W. E. Homogenization of linear and nonlinear transport equations. Comm. Pure Appl. Math., 45(3):301–326, 1992.

    Article  MathSciNet  Google Scholar 

  29. B. Engquist and E. Luo. Convergence of a multigrid method for elliptic equations with highly oscillatory coefficients. SIAM J. Numer. Anal., 34(6):2254–2273, 1997.

    Article  MATH  MathSciNet  Google Scholar 

  30. B. Engquist and O. Runborg. Wavelet-based numerical homogenization with applications. In T. J. Barth, T. F. Chan, and R. Haimes, editors, Multiscale and Multiresolution Methods, volume 20 of Lect. Notes Comput. Sci. Eng., pages 97–148. Springer, Berlin, 2002.

    Google Scholar 

  31. J. Geronimo, D. Hardin, and P. R. Massopust. Fractal functions and wavelet expansions based on several scaling functions. J. Approx. Theory, 78(3):373–401, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  32. A. C. Gilbert. A comparison of multiresolution and classical one-dimensional homoge-nization schemes. Appl. Comput. Harmon. Anal.., 5(1):1–35, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  33. A. Grossmann and J. Morlet. Decompostion of Hardy functions into square integrable wavelets of constant shape. SIAM J. Math. Anal., 15(4):723–736, 1984.

    Article  MATH  MathSciNet  Google Scholar 

  34. A. Haar. Zur Theorie der orthogonalen Funktionen-Systeme. Math. Ann., 69:331–371, 1910.

    Article  MATH  MathSciNet  Google Scholar 

  35. A. Harten. Adaptive multiresolution schemes for shock computations. J. Comput. Phys., 115(2):319–338, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  36. T. Y. Hou and X. H. Wu. A multiscale finite element method for elliptic problems in composite materials and porous media. J. Comput. Phys., 134(1):169–189, 1997.

    Article  MATH  MathSciNet  Google Scholar 

  37. T. Y. Hou and X. Xin. Homogenization of linear transport equations with oscillatory vector fields. SIAM J. Appl. Math., 52(1):34–45, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  38. T. J. R. Hughes. Multiscale phenomena: Green's functions, the Dirichlet-to Neumann formulation, subgrid, scale models, bubbles and the origins of stabilized methods. Comput. Methods Appl. Mech. Engrg., 127:387–401, 1995.

    Article  MATH  MathSciNet  Google Scholar 

  39. B. Jawerth and W. Sweldens. An overview of wavelet based multiresolution analyses. SIAM Rev., 36(3):377–412, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  40. J. Keller. Geometrical theory of diffraction. J. Opt. Soc. Amer., 52, 1962.

    Google Scholar 

  41. S. Knapek. Matrix-dependent multigrid-homogenization for diffusion problems. SIAM J. Sci. Stat. Comp., 20(2):515–533, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  42. J. Krishnan, O. Runborg, and I.G. Kevrekidis. Bifurcation analysis of nonlinear reaction-diffusion problems using wavelet-based reduction techniques. Comput. Chem. Eng., 28:557–574, 2004.

    Article  Google Scholar 

  43. P.-G. Lemarié. Une nouvelle base d'ondelettes de L 2(R). J. Math. Pures Appl., 67(3):227–236, 1988.

    MATH  MathSciNet  Google Scholar 

  44. D. D. Leon. Wavelet Operators Applied to Multigrid Methods. PhD thesis, Department of Mathematics, UCLA, 2000.

    Google Scholar 

  45. S. G. Mallat. Multiresolution approximations and wavelet orthonormal bases of L 2(R). Trans. Amer. Math. Soc., 315(1):69–87, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  46. Y. Meyer. Principe d'incertitude, bases Hilbertiennes at algébres d'opérateurs. Séminaire Bourbaki 662, 1985–1986.

    Google Scholar 

  47. Y. Meyer. Ondelettes et fonctions splines. Séminaire équations aux dérivées partielles 6, É cole Polytechnique, 1986–1987.

    Google Scholar 

  48. Y. Meyer. Wavelets: Algorithms and Applications. SIAM, Philadelphia, PA, 1993.

    Google Scholar 

  49. N. Neuss, W. Jäger, and G. Wittum. Homogenization and multigrid. Computing, 66(1):1– 26, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  50. P.-O. Persson and O. Runborg. Simulation of a waveguide filter using wavelet-based numerical homogenization. J. Comput. Phys., 166:361–382, 2001.

    Article  MATH  Google Scholar 

  51. G. Strang and T. Nguyen. Wavelets and Filter Banks. Wellesley, Cambridge, 1996.

    Google Scholar 

  52. J. O. Strömberg. A modified Franklin system and higher order spline systems on R n as unconditional bases for Hardy spaces. In Beckner et al., editor, Conference on Harmonic Analysis in Honor of Antoni Zygmund, volume II, pages 475–494, Chicago, 1981. Univ. of Chicago Press.

    Google Scholar 

  53. W. Sweldens. The lifting scheme: A construction of second generation wavelets. SIAM J. Math. Anal., 29(2):511–546, 1997.

    Article  MathSciNet  Google Scholar 

  54. A. Taflove. Computational Electromagnetics, The Finite-Difference Time-Domain Method, chapter 10. Artech House, 1995.

    Google Scholar 

  55. C.-M. Wang. Wavelet-Based Numerical Homogenization with Application to Flow in Porous Media. PhD thesis, Department of Mathematics, UCLA, 2005.

    Google Scholar 

  56. D. Wilcox. Turbulence Modeling for CFD. DCW Industries, Inc., 1993.

    Google Scholar 

  57. J.-C. Xu and W.-C. Shann. Galerkin-wavelet methods for two-point boundary value problems. Numer. Math., 63(1):123–142, 1992.

    Article  MATH  MathSciNet  Google Scholar 

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Runborg, O. (2009). Wavelets andWavelet Based Numerical Homogenization. In: Engquist, B., Lötstedt, P., Runborg, O. (eds) Multiscale Modeling and Simulation in Science. Lecture Notes in Computational Science and Engineering, vol 66. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88857-4_4

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