Numerical Methods in Engineering With Python First Edition by Jaan Kiusalaas ISBN 978-0521852876 0521852870

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Product details: 

ISBN 10:   0521852870

ISBN 13: 978-0521852876

Author:  Jaan Kiusalaas
Numerical Methods in Engineering with Python is a text for engineering students and a reference for practicing engineers, especially those who wish to explore the power and efficiency of Python. Examples and applications were chosen for their relevance to real world problems, and where numerical solutions are most efficient. Numerical methods are discussed thoroughly and illustrated with problems involving both hand computation and programming. Computer code accompanies each method and is available on the book web site. This code is made simple and easy to understand by avoiding complex bookkeeping schemes, while maintaining the essential features of the method. Python was chosen as the example language because it is elegant, easy to learn and debug, and its facilities for handling arrays are unsurpassed. Moreover, it is an open-source software package; free and available to all students and engineers. Explore numerical methods with Python, a great language for teaching scientific computation.

Table of contents: 

1. Core Python and Program Structure

1. General Information

2. Core Python

3. Functions and Modules

4. Mathematics Modules

5. numarray Module

6. Scoping of Variables

7. Writing and Running Programs

2. Solving Linear Systems
8. Introduction
9. Gauss Elimination Method
10. LU Decomposition Methods
11. Symmetric and Banded Coefficient Matrices
12. Pivoting
13. Matrix Inversion
14. Iterative Methods
15. Other Methods

3. Interpolation and Curve Fitting
16. Introduction
17. Polynomial Interpolation
18. Interpolation with Cubic Spline
19. Least-Squares Fit
20. Other Methods

4. Solving Nonlinear Equations
21. Introduction
22. Incremental Search Method
23. Method of Bisection
24. Brent’s Method
25. Newton–Raphson Method
26. Systems of Equations
27. Zeroes of Polynomials
28. Other Methods

5. Numerical Differentiation
29. Introduction
30. Finite Difference Approximations
31. Richardson Extrapolation
32. Derivatives by Interpolation

6. Numerical Integration
33. Introduction
34. Newton–Cotes Formulas
35. Romberg Integration
36. Gaussian Integration
37. Multiple Integrals

7. Solving Initial Value Problems
38. Introduction
39. Taylor Series Method
40. Runge–Kutta Methods
41. Stability and Stiffness
42. Adaptive Runge–Kutta Method
43. Bulirsch–Stoer Method
44. Other Methods

8. Solving Boundary Value Problems
45. Introduction
46. Shooting Method
47. Finite Difference Method

9. Eigenvalue Problems
48. Introduction
49. Jacobi Method
50. Inverse Power and Power Methods
51. Householder Reduction to Tridiagonal Form
52. Eigenvalues of Symmetric Tridiagonal Matrices
53. Other Methods

10. Optimization
54. Introduction
55. Minimization Along a Line
56. Conjugate Gradient Methods
57. Other Methods

11. Supplementary Materials
58. Appendices
59. Index

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Tags: Jaan Kiusalaas, Numerical Methods, Engineering With Python