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Numerical Solution of Ordinary Differential Equations / Edition 1

Numerical Solution of Ordinary Differential Equations / Edition 1


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Product Details

ISBN-13: 9780470042946
Publisher: Wiley
Publication date: 02/09/2009
Series: Pure and Applied Mathematics: A Wiley Series of Texts, Monographs and Tracts Series , #81
Edition description: New Edition
Pages: 272
Product dimensions: 6.30(w) x 9.30(h) x 0.80(d)

About the Author

Kendall E. Atkinson, PhD, is Professor Emeritus in the Departments of Mathematics and Computer Science at the University of Iowa. He has authored books and journal articles in his areas of research interest, which include the numerical solution of integral equations and boundary integral equation methods. Weimin Han, PhD, is Professor in the Department of Mathematics at the University of Iowa, where he is also Director of the interdisciplinary PhD Program in Applied Mathematical and Computational Science. Dr. Han currently focuses his research on the numerical solution of partial differential equations. David E. Stewart, PhD, is Professor and Associate Chair in the Department of Mathematics at the University of Iowa, where he is also the departmental Director of Undergraduate Studies. Dr. Stewart's research interests include numerical analysis, computational models of mechanics, scientific computing, and optimization.

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Table of Contents



1. Theory of differential equations: an introduction.

1.1 General solvability theory.

1.2 Stability of the initial value problem.

1.3 Direction fields.


2. Euler’s method.

2.1 Euler’s method.

2.2 Error analysis of Euler’s method.

2.3 Asymptotic error analysis.

2.3.1 Richardson extrapolation.

2.4 Numerical stability.

2.4.1 Rounding error accumulation.


3. Systems of differential equations.

3.1 Higher order differential equations.

3.2 Numerical methods for systems.


4. The backward Euler method and the trapezoidalmethod.

4.1 The backward Euler method.

4.2 The trapezoidal method.


5. Taylor and Runge-Kutta methods.

5.1 Taylor methods.

5.2 Runge-Kutta methods.

5.3 Convergence, stability, and asymptotic error.

5.4 Runge-Kutta-Fehlberg methods.

5.5 Matlab codes.

5.6 Implicit Runge-Kutta methods.


6. Multistep methods.

6.1 Adams-Bashforth methods.

6.2 Adams-Moulton methods.

6.3 Computer codes.


7. General error analysis for multistep methods.

7.1 Truncation error.

7.2 Convergence.

7.3 A general error analysis.


8. Stiff differential equations.

8.1 The method of lines for a parabolic equation.

8.2 Backward differentiation formulas.

8.3 Stability regions for multistep methods.

8.4 Additional sources of difficulty.

8.5 Solving the finite difference method.

8.6 Computer codes.


9. Implicit RK methods for stiff differentialequations.

9.1 Families of implicit Runge-Kutta methods.

9.2 Stability of Runge-Kutta methods.

9.3 Order reduction.

9.4 Runge-Kutta methods for stiff equations in practice.


10. Differential algebraic equations.

10.1 Initial conditions and drift.

10.2 DAEs as stiff differential equations.

10.3 Numerical issues: higher index problems.

10.4 Backward differentiation methods for DAEs.

10.5 Runge-Kutta methods for DAEs.

10.6 Index three problems from mechanics.

10.7 Higher index DAEs.


11. Two-point boundary value problems.

11.1 A finite difference method.

11.2 Nonlinear two-point boundary value problems.


12. Volterra integral equations.

12.1 Solvability theory.

12.2 Numerical methods.

12.3 Numerical methods - Theory.


Appendix A. Taylor’s theorem.

Appendix B. Polynomial interpolation.



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