Skip to main content
Log in

Higher order numerical differentiation on the Infinity Computer

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

There exist many applications where it is necessary to approximate numerically derivatives of a function which is given by a computer procedure. In particular, all the fields of optimization have a special interest in such a kind of information. In this paper, a new way to do this is presented for a new kind of a computer—the Infinity Computer—able to work numerically with finite, infinite, and infinitesimal numbers. It is proved that the Infinity Computer is able to calculate values of derivatives of a higher order for a wide class of functions represented by computer procedures. It is shown that the ability to compute derivatives of arbitrary order automatically and accurate to working precision is an intrinsic property of the Infinity Computer related to its way of functioning. Numerical examples illustrating the new concepts and numerical tools are given.

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. Berz, M.: Automatic differentiation as nonarchimedean analysis. In: Computer Arithmetic and Enclosure Methods. pp. 439–450. Elsevier, Amsterdam (1992)

  2. Bischof, C., Bücker, M.: Computing derivatives of computer programs. In: Modern Methods and Algorithms of Quantum Chemistry Proceedings NIC Series, vol. 3, 2 edn, pp. 315–327. John von Neumann Institute for Computing, Jülich (2000)

  3. Chua L.O., Desoer C.A., Kuh E.S.: Linear and Non linear Circuits. MacGraw Hill, Singapore (1987)

    Google Scholar 

  4. Cohen J.S.: Computer Algebra and Symbolic Computation: Mathematical Methods. A K Peters, Ltd, Wellesley (1966)

    Google Scholar 

  5. Corliss, G., Faure, C., Griewank, A., Hascoet, L., Naumann, U. (eds): Automatic Differentiation of Algorithms: From Simulation to Optimization. Springer, New York (2002)

    MATH  Google Scholar 

  6. Daponte P., Grimaldi D., Molinaro A., Sergeyev Ya.D.: An algorithm for finding the zero-crossing of time signals with lipschitzian derivatives. Measurement 16, 37–49 (1995)

    Article  Google Scholar 

  7. Lam H.Y.-F.: Analog and Digital Filters-Design and Realization. Prentice Hall Inc, New Jersey (1979)

    Google Scholar 

  8. Lyness J.N., Moler C.B.: Numerical differentiation of analytic functions. SIAM J. Numer. Anal. 4, 202–210 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  9. Moin P.: Fundamentals of Engineering Numerical Analysis. Cambridge University Press, Cambridge (2001)

    MATH  Google Scholar 

  10. Muller J.M.: Elementary Functions: Algorithms and Implementation. Birkhäuser, Boston (2006)

    MATH  Google Scholar 

  11. Pardalos, P.M., Resende, M.G.C. (eds): Handbook of Applied Optimization. Oxford University Press, New York (2002)

    MATH  Google Scholar 

  12. Sergeyev Ya.D.: Arithmetic of Infinity. Edizioni Orizzonti Meridionali, CS (2003)

    MATH  Google Scholar 

  13. Sergeyev, Ya.D.: http://www.theinfinitycomputer.com (2004)

  14. Sergeyev Ya.D.: A new applied approach for executing computations with infinite and infinitesimal quantities. Informatica 19(4), 567–596 (2008)

    MathSciNet  MATH  Google Scholar 

  15. Sergeyev, Ya.D.: Computer system for storing infinite, infinitesimal, and finite quantities and executing arithmetical operations with them. EU patent 1728149, (2009)

  16. Sergeyev Ya.D.: Numerical computations and mathematical modelling with infinite and infinitesimal numbers. J. Appl. Math. Comput. 29, 177–195 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  17. Sergeyev Ya.D.: Numerical point of view on Calculus for functions assuming finite, infinite, and infinitesimal values over finite, infinite, and infinitesimal domains. Nonlinear Anal. Ser. A Theory Methods Appl. 71(12), e1688–e1707 (2009)

    Article  MathSciNet  Google Scholar 

  18. Sergeyev Ya.D., Daponte P., Grimaldi D., Molinaro A.: Two methods for solving optimization problems arising in electronic measurements and electrical engineering. SIAM J. Optim. 10(1), 1–21 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  19. Sergeyev, Ya.D., Kvasov, D.E.: Diagonal Global Optimization Methods. Fizmatlit, Moscow (2008, in Russian)

  20. Strongin R.G., Sergeyev Ya.D.: Global Optimization and Non-Convex Constraints: Sequential and Parallel Algorithms. Kluwer Academic Publishers, Dordrecht (2000)

    MATH  Google Scholar 

  21. Walnut D.F.: An Introduction to Wavelet Analysis. Birkhäuser, Boston (2004)

    Google Scholar 

  22. Wilf H.S.: Generatingfunctionology, 3rd edn. A K Peters, Ltd., Wellesley (2006)

    MATH  Google Scholar 

  23. Wolfe M.A.: On first zero crossing points. Appl. Math. Comput. 150, 467–479 (2004)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yaroslav D. Sergeyev.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sergeyev, Y.D. Higher order numerical differentiation on the Infinity Computer. Optim Lett 5, 575–585 (2011). https://doi.org/10.1007/s11590-010-0221-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-010-0221-y

Keywords

Navigation