Skip to main content
Log in

Reconstruction and Collocation of a Class of Non-periodic Functions by Sampling Along Tent-Transformed Rank-1 Lattices

  • Published:
Journal of Fourier Analysis and Applications Aims and scope Submit manuscript

Abstract

Spectral collocation and reconstruction methods have been widely studied for periodic functions using Fourier expansions. We investigate the use of cosine series for the approximation and collocation of multivariate non-periodic functions with frequency support mainly determined by hyperbolic crosses. We seek methods that work for an arbitrary number of dimensions. We show that applying the tent-transformation on rank-1 lattice points renders them suitable to be collocation/sampling points for the approximation of non-periodic functions with perfect numerical stability. Moreover, we show that the approximation degree—in the sense of approximating inner products of basis functions up to a certain degree exactly—of the tent-transformed lattice point set with respect to cosine series, is the same as the approximation degree of the original lattice point set with respect to Fourier series, although the error can still be reduced in the case of cosine series. A component-by-component algorithm is studied to construct such a point set. We are then able to reconstruct a non-periodic function from its samples and approximate the solutions to certain PDEs subject to Neumann and Dirichlet boundary conditions. Finally, we present some numerical results.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Adcock, B.: Multivariate modified Fourier series and application to boundary value problems. Numerische Mathematik 115, 511–552 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  2. Adcock, B., Huybrechs, D.: Multivariate modified Fourier expansions. In: Proceedings of the International Conference on Spectral and High Order Methods, vol. 76, pp. 85–92 (2011)

  3. Boyd, J.P.: Chebyshev and Fourier Spectral Methods. Courier Dover Publications, Mineola (2001)

    MATH  Google Scholar 

  4. Bungartz, H.-J., Griebel, M.: Sparse grids. Acta Numer. 13, 1–123 (2004)

    Article  MathSciNet  Google Scholar 

  5. Cools, R., Kuo, F.Y., Nuyens, D.: Constructing lattice rules based on weighted degree of exactness and worst case error. Computing 87, 63–89 (2010)

  6. Cools, R., Nuyens, D.: A Belgian view on lattice rules. In: Keller, A., Heinrich, S., Niederreiter, H.(eds.) Monte Carlo and Quasi-Monte Carlo Methods 2006, pp. 3–21. Springer, Berlin (2008)

  7. Dick, J., Kuo, F.Y., Sloan, I.H.: High-dimensional integration: the quasi-Monte Carlo way. Acta Numer. 22, 133–288 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  8. Dick, J., Nuyens, D., Pillichshammer, F.: Lattice rules for nonperiodic smooth integrands. Numerische Mathematik 126, 259–291 (2013)

    Article  MathSciNet  Google Scholar 

  9. Hickernell, F.J.: Obtaining O\((n^{-2+\epsilon })\) convergence for lattice quadrature rules. In: Fang, K.T., Hickernell, F.J., Niederreiter, H. (eds.) Monte Carlo and Quasi-Monte Carlo Methods 2000, pp. 274–289 (2002)

  10. Iserles, A., Nørsett, S.P.: Modified Fourier expansions: from high oscillation to rapid approximation I.IMA J. Numer. Anal. 28, 862–887 (2008)

  11. Kämmerer, L., Kunis, S.: On the stability of the hyperbolic cross discrete Fourier transform. Numerische Mathematik 117, 581–600 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  12. Kämmerer, L., Kunis, S., Potts, D.: Interpolation lattices for hyperbolic cross trigonometric polynomials. J. Complex. 28, 76–92 (2012)

    Article  MATH  Google Scholar 

  13. Kämmerer, L.: Reconstructing hyperbolic cross trigonometric polynomials by sampling along rank-1 lattices. SIAM J. Numer. Anal. 51(5), 2773–2796 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  14. Keng, H.L., Yuan, W.: Applications of Number Theory to Numerical Analysis. Springer, New York (1981)

    Book  MATH  Google Scholar 

  15. Kuo, F.Y., Sloan, I.H., Woźniakowski, H.: Lattice rules for multivariate approximation in the worst case setting. In: Niederreiter, H., Talay, D. (eds.), Monte Carlo and Quasi-Monte Carlo Methods 2004, pp. 289–330 (2006)

  16. Li, D., Hickernell, F.J.: Trigonometric spectral collocation methods on lattices. In: Cheng, S.Y., Shu, C.-W., Tang, T. (eds.) Recent Advances in Scientific Computing and Partial Differential Equations. AMS Series in Contemporary Mathematics, vol. 330, pp. 121–132. American Mathematical Society, Providence (2003)

    Chapter  Google Scholar 

  17. Munthe-Kaas, H., Sørevik, T.: Multidimensional pseudo-spectral methods on lattice grids. Appl. Numer. Math. 62(3), 155–165 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  18. Nuyens, D.: The construction of good lattice rules and polynomial lattice rules. In: Kritzer, P., Niederreiter, H., Pillichshammer, F., Winterhof, A. (eds.) Uniform Distribution and Quasi-Monte Carlo Methods: Discrepancy, Integration and Applications. Radon Series on Computational and Applied Mathematics, vol. 15, pp. 223–256. De Gruyter, Berlin (2014)

    Google Scholar 

  19. Olver, S.: On the convergence rate of a modified Fourier series. Math. Comput. 78, 1629–1645 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  20. Ruijter, M.J., Oosterlee, C.W., Aalbers, R.F.T.: On the Fourier cosine series expansion (COS) method for stochastic control problems. Numer. Linear Algebra Appl. 20(4), 598–625 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  21. Sloan, I.H., Joe, S.: Lattice Methods for Multiple Integration. Oxford University Press, Oxford (1994)

    MATH  Google Scholar 

  22. Sloan, I.H., Woźniakowski, H.: When are quasi-Monte Carlo algorithms efficient for high dimensional integrals? J. Complex. 14, 1–33 (1998)

    Article  MATH  Google Scholar 

Download references

Acknowledgments

We thank Daan Huybrechs for his comments on the initial transcripts of the paper. We thank Dirk Abbeloos for some of his valuable tips on PDEs. We also thank our anonymous referees for their constructive review comments. We thank the ICERM organization at Brown University for their kind hospitality during the semester program for High-dimensional Approximation, many ideas to improve this manuscript came while working in the vast collaborative spaces they provided.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gowri Suryanarayana.

Additional information

Communicated by Arieh Iserles.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Suryanarayana, G., Nuyens, D. & Cools, R. Reconstruction and Collocation of a Class of Non-periodic Functions by Sampling Along Tent-Transformed Rank-1 Lattices. J Fourier Anal Appl 22, 187–214 (2016). https://doi.org/10.1007/s00041-015-9412-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00041-015-9412-3

Keywords

Mathematics Subject Classification

Navigation