IDEAS home Printed from https://ideas.repec.org/b/oxp/obooks/9780198527718.html
   My bibliography  Save this book

Applied Partial Differential Equations

Author

Listed:
  • Ockendon, John

    (OCIAM, University of Oxford)

  • Howison, Sam

    (OCIAM, University of Oxford)

  • Lacey, Andrew

    (Department of Mathematics, Heriot-Watt University)

  • Movchan, Alexander

    (Department of Mathematics, University of Liverpool)

Abstract

Partial differential equations are a central concept in mathematics. They are used in mathematical models of a huge range of real-world phenomena, from electromagnetism to financial markets. This new edition of the well-known text by Ockendon et al., providing an enthusiastic and clear guide to the theory and applications of PDEs, provides timely updates on: transform methods (especially multidimensional Fourier transforms and the Radon transform); explicit representations of general solutions of the wave equation; bifurcations; the Wiener-Hopf method; free surface flows; American options; the Monge-Ampere equation; linear elasticity and complex characteristics; as well as numerous topical exercises. This book is ideal for students of mathematics, engineering and physics seeking a comprehensive text in the modern applications of PDEs

Suggested Citation

  • Ockendon, John & Howison, Sam & Lacey, Andrew & Movchan, Alexander, 2003. "Applied Partial Differential Equations," OUP Catalogue, Oxford University Press, number 9780198527718.
    • Handle: RePEc:oxp:obooks:9780198527718
    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 search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yao, Haixiang & Yang, Zhou & Chen, Ping, 2013. "Markowitz’s mean–variance defined contribution pension fund management under inflation: A continuous-time model," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 851-863.
    2. Zafar Ahmad & Reilly Browne & Rezaul Chowdhury & Rathish Das & Yushen Huang & Yimin Zhu, 2023. "Fast American Option Pricing using Nonlinear Stencils," Papers 2303.02317, arXiv.org, revised Oct 2023.
    3. Ruslan Voropai & Abebe Geletu & Pu Li, 2023. "Model Predictive Control of Parabolic PDE Systems under Chance Constraints," Mathematics, MDPI, vol. 11(6), pages 1-23, March.

    More about this item

    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:oxp:obooks:9780198527718. 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: Economics Book Marketing (email available below). General contact details of provider: http://www.oup.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.