Buch, Englisch, 784 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1565 g
Reihe: Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series
With Pseudocodes
Buch, Englisch, 784 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1565 g
Reihe: Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series
ISBN: 978-1-032-75474-1
Verlag: CRC Press
Numerical Methods for Scientists and Engineers: With Pseudocodes is designed as a primary textbook for a one-semester course on Numerical Methods for sophomore or junior-level students. It covers the fundamental numerical methods required for scientists and engineers, as well as some advanced topics which are left to the discretion of instructors.
The objective of the text is to provide readers with a strong theoretical background on numerical methods encountered in science and engineering, and to explain how to apply these methods to practical, real-world problems. Readers will also learn how to convert numerical algorithms into running computer codes.
Features:
- Numerous pedagogic features including exercises, “pros and cons” boxes for each method discussed, and rigorous highlighting of key topics and ideas
- Suitable as a primary text for undergraduate courses in numerical methods, but also as a reference to working engineers
- A Pseudocode approach that makes the book accessible to those with different (or no) coding backgrounds, which does not tie instructors to one particular language over another
- A dedicated website featuring additional code examples, quizzes, exercises, discussions, and more: https://github.com/zaltac/NumMethodsWPseudoCodes
- A complete Solution Manual and PowerPoint Presentations are available (free of charge) to instructors at www.routledge.com/9781032754741
Zielgruppe
Undergraduate Core
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Numerical Algorithms and Errors. 2. Linear Systems: Fundamentals and Direct Methods. 3. Linear Systems: Iterative Methods. 4. Nonlinear Equations. 5. Numerical Differentiation. 6. Interpolation and Extrapolation. 7. Least Squares Regression. 8. Numerical Integration. 9. ODEs: Initial Value Problems. 10. ODEs: Boundary Value Problems. 11. Eigenvalues and Eigenvalue Problems.