IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-60218-4_3.html

An Automatic Symbolic-Numeric Taylor Series ODE Solver

In: Computer Algebra in Scientific Computing CASC’99

Author

Listed:
  • Brian J. Dupée

    (University of Bath, Department of Mathematical Sciences)

  • James H. Davenport

    (University of Bath, Department of Mathematical Sciences)

Abstract

One of the basic techniques in every mathematician’s toolkit is the Taylor series representation of functions. It is of such fundamental importance and it is so well understood that its use is often a first choice in numerical analysis. This faith has not, unfortunately, been transferred to the design of computer algorithms. Approximation by use of Taylor series methods is inherently partly a symbolic process and partly numeric. This aspect has often, with reason, been regarded as a major hindrance in algorithm design. Whilst attempts have been made in the past to build a consistent set of programs for the symbolic and numeric paradigms, these have been necessarily multi-stage processes. Using current technology it has at last become possible to integrate these two concepts and build an automatic adaptive symbolic-numeric algorithm within a uniform framework which can hide the internal workings behind a modern interface.

Suggested Citation

  • Brian J. Dupée & James H. Davenport, 1999. "An Automatic Symbolic-Numeric Taylor Series ODE Solver," Springer Books, in: Victor G. Ganzha & Ernst W. Mayr & Evgenii V. Vorozhtsov (ed.), Computer Algebra in Scientific Computing CASC’99, pages 37-50, Springer.
  • Handle: RePEc:spr:sprchp:978-3-642-60218-4_3
    DOI: 10.1007/978-3-642-60218-4_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-642-60218-4_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.