Numerical Methods in Engineering with PythonCambridge University Press, 29.01.2010 This text is for engineering students and a reference for practising engineers, especially those who wish to explore Python. This new edition features 18 additional exercises and the addition of rational function interpolation. Brent's method of root finding was replaced by Ridder's method, and the Fletcher-Reeves method of optimization was dropped in favor of the downhill simplex method. Each numerical method is explained in detail, and its shortcomings are pointed out. The examples that follow individual topics fall into two categories: hand computations that illustrate the inner workings of the method and small programs that show how the computer code is utilized in solving a problem. This second edition also includes more robust computer code with each method, which is available on the book website. This code is made simple and easy to understand by avoiding complex bookkeeping schemes, while maintaining the essential features of the method. |
Inhalt
Interpolation and Curve Fitting | 99 |
Numerical Differentiation | 177 |
Numerical Integration | 193 |
Initial Value Problems | 243 |
TwoPoint Boundary Value Problems | 290 |
Symmetric Matrix Eigenvalue Problems | 319 |
Introduction to Optimization | 374 |
Roots of Equations | 377 |
List of Program Modules by Chapter | 416 |
Andere Ausgaben - Alle anzeigen
Häufige Begriffe und Wortgruppen
abscissas algorithm back substitution beam bisection boundary conditions boundary value problem bracketed coefficient matrix column Compute constraints convergence data points decimal places derivatives determine diagonal differential equation displacement dx dy eigenvalue problem eigenvectors elements evaluate EXAMPLE finite difference approximations function Gauss elimination Gauss-Legendre quadrature Gaussian initial conditions initial value problem integration formulas inverse power method iterations Jacobi method k₁ linear LU decomposition math import sqrt minimization module nodes numerical integration numpy import array O(h² obtained panels pivot plot Pn(x polynomial interpolation printSoln Prob PROBLEM SET Python quadrilateral range(n raw_input("\nPress return return to exit Richardson extrapolation Romberg integration root Runge-Kutta method shown smallest eigenvalues symmetric Symmetric Matrix Table Taylor series trapezoidal rule triangular tridiagonal tridiagonal matrix truncation error usr/bin/python vector X₁ Xi+1 xStop yields zero ΕΙ Уз