Skip to main content
Log in

Faster than the Fast Legendre Transform, the Linear-time Legendre Transform

  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

A new algorithm to compute the Legendre–Fenchel transform is proposed and investigated. The so-called Linear-time Legendre Transform (LLT) improves all previously known Fast Legendre Transform algorithms by reducing their log-linear worst-case time complexity to linear. Since the algorithm amounts to computing several convex hulls and sorting, any convex hull algorithm well-suited for a particular problem gives a corresponding LLT algorithm. After justifying the convergence of the Discrete Legendre Transform to the Legendre–Fenchel transform, an extended computation time complexity analysis is given and confirmed by numerical tests. Finally, the LLT is illustrated with several examples and a LLT MATLAB package is described.

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. Y. Brenier, Un algorithme rapide pour le calcul detransformée de Legendre-Fenchel discrètes, C. R. Acad. Sci. Paris Sér. I Math. 308 (1989) 587–589.

    MATH  MathSciNet  Google Scholar 

  2. R.M. Corless, G.H. Gonnet, D.E.G. Hare, D.J. Jeffrey and D.E. Knuth, On the Lambert W function, Adv. Comput. Math. 5 (1996) 329–359.

    MATH  MathSciNet  Google Scholar 

  3. L. Corrias, Fast Legendre-Fenchel transform and applications to Hamilton-Jacobi equations and conservation laws, SIAM J. Numer. Anal. 33 (1996) 1534–1558.

    Article  MATH  MathSciNet  Google Scholar 

  4. H. Edelsbrunner, Algorithms in Combinatorial Geometry,EATC Monographs on Theoretical Computer Science (Springer, Berlin, 1987).

    Google Scholar 

  5. J.-B. Hiriart-Urruty, Lipschitz r-continuity of the approximatesubdifferential of a convex function, Math. Scand. 47 (1980) 123–134.

    MATH  MathSciNet  Google Scholar 

  6. J.-B. Hiriart-Urruty and C. Lemaréchal, Convex Analysisand Minimization Algorithms, A Series of Comprehensive Studies in Mathematics (Springer, Berlin, 1993).

    Google Scholar 

  7. D.E. Knuth, The Art of ComputerProgramming, Vol. 3: Sorting and Searching, Series in Computer Science and Information Processing (Addison-Wesley, Reading, MA, 1973).

    Google Scholar 

  8. Y. Lucet, A fast computational algorithm for the Legendre-Fenchel transform, Comput. Optim. Appl. 6 (1996) 27–57.

    Article  MATH  MathSciNet  Google Scholar 

  9. Y. Lucet, Latransformée de Legendre-Fenchel et la convexifiée d'une fonction: algorithmes rapides de calcul, analyse et régularité du second ordre, Ph.D. thesis, Laboratoire Approximation et Optimisation, Université Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse Cedex 4, France (February 1997).

    Google Scholar 

  10. A. Noullez and M. Vergassola, A fastLegendre transform algorithm and applications to the adhesion model, J. Sci. Comput. 9 (1994) 259–281.

    Article  MATH  MathSciNet  Google Scholar 

  11. P. Plazanet, Contributionà l'analyse des fonctions convexes et des différences de fonctions convexes. Applications à l'optimisation et à la théorie des E.D.P., Ph.D. thesis, Laboratoire d'Analyse Numérique, Université Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse Cedex 4, France (1990).

    Google Scholar 

  12. F.P. Preparata and M.I. Shamos,Computational Geometry, Texts and Monographs in Computer Science (Springer, Berlin, 3rd ed., 1990).

    Google Scholar 

  13. R.T. Rockafellar, ConvexAnalysis (Princeton University Press, Princeton, 1970).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lucet, Y. Faster than the Fast Legendre Transform, the Linear-time Legendre Transform. Numerical Algorithms 16, 171–185 (1997). https://doi.org/10.1023/A:1019191114493

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1019191114493

Navigation