The Essentials of Numerical Computation |
Contents
Some Fundamental Ideas in Numerical Computation | 1 |
Interpolation in Tabulated Functions | 25 |
Least Squares Approximation of Tabulated Functions and Data | 48 |
Copyright | |
7 other sections not shown
Common terms and phrases
accuracy algorithm analytical apply approach arithmetic augmented matrix bisection calculation chapter column computed consider convergence cubic curve denotes diagonal differential equation dy/dx eigenvalue eigenvectors element error estimate Euler's method example EXERCISES expressed f x,x factors finite difference formula function f(x Gauss-Seidel Gauss-Seidel method Gaussian elimination given gives go to step gradient method Hence i+1 i+1 idea integral inverse involves least squares approximation linear equations mathematical minimize minimum model function modified Euler Newton's method nonlinear equations numerical obtain order Runge-Kutta method procedure QR algorithm quadratic function relative error residuals result root rounding error Runge-Kutta method secant method shooting method significant figures simple Simpson's rule smallest eigenvalue solve the equations spline straight line Suppose tabulated function Taylor series technique trapezoidal rule trial variables vector Write a program x-values y(x+h zero