Ulteriori informazioni
Striking a balance between theory and practice, this graduate-level text is perfect for students in the applied sciences. The author provides a clear introduction to the classical methods, how they work and why they sometimes fail. Crucially, he also demonstrates how these simple and classical techniques can be combined to address difficult problems. Many worked examples and sample programs are provided to help the reader make practical use of the subject material. Further mathematical background, if required, is summarized in an appendix. Topics covered include classical methods for linear systems, eigenvalues, interpolation and integration, ODEs and data fitting, and also more modern ideas like adaptivity and stochastic differential equations.
Sommario
Preface; 1. Numerical error; 2. Direct solution of linear systems; 3. Eigenvalues and eigenvectors; 4. Iterative approaches for linear systems; 5. Interpolation; 6. Iterative methods and the roots of polynomials; 7. Optimization; 8. Data fitting; 9. Integration; 10. Ordinary differential equations; 11. Introduction to stochastic ODEs; 12. A big integrative example; A. Mathematical background; B. Answers; C. Sample codes; References; Index.
Info autore
G. Miller is a professor in the Department of Chemical Engineering and Materials Science at the University of California, Davis.
Riassunto
Striking a balance between theory and practice, this graduate-level text is perfect for students in the applied sciences. It provides full coverage of classical methods with a clear explanation of how they work, together with sample programs and many practical examples to help students get started.
