Numerical Methods for Ordinary Differential Equations, Second Edition

Numerical Methods for Ordinary Differential Equations, Second Edition

Author(s): J. C. Butcher

Published Online: 18 MAR 2008

Print ISBN: 9780470723357

Online ISBN: 9780470753767

DOI: 10.1002/9780470753767

About this Book

In recent years the study of numerical methods for solving ordinary differential equations has seen many new developments. This second edition of the author's pioneering text is fully revised and updated to acknowledge many of these developments.  It includes a complete treatment of linear multistep methods whilst maintaining its unique and comprehensive emphasis on Runge-Kutta methods and general linear methods.

Although the specialist topics are taken to an advanced level, the entry point to the volume as a whole is not especially demanding.  Early chapters provide a wide-ranging introduction to differential equations and difference equations together with a survey of numerical differential equation methods, based on the fundamental Euler method with more sophisticated methods presented as generalizations of Euler.

Features of the book include

  • Introductory work on differential and difference equations.
  • A comprehensive introduction to the theory and practice of solving ordinary differential equations numerically.
  • A detailed analysis of Runge-Kutta methods and of linear multistep methods.
  • A complete study of general linear methods from both theoretical and practical points of view.
  • The latest results on practical general linear methods and their implementation.
  • A balance between informal discussion and rigorous mathematical style.
  • Examples and exercises integrated into each chapter enhancing the suitability of the book as a course text or a self-study treatise.

Written in a lucid style by one of the worlds leading authorities on numerical methods for ordinary differential equations and drawing upon his vast experience, this new edition provides an accessible and self-contained introduction, ideal for researchers and students following courses on numerical methods, engineering and other sciences.

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