In the following table, each line/entry contains the name of the computer file and a brief description. Click on the program name to display the source code, which can be downloaded.
Chapter 1: Introduction | ||
sineplot.m | Graph of Taylor series partial sums for sin(x) (invoking s1.m, s2.m, s3.m) | |
sqrt_approx.m | Variable precision arithmetic for approximation | |
Chapter 2: Number Representation and Errors | ||
format.m | Numbers in different formats | |
accuracy.m | Numbers with different accuracy | |
Chapter 3: Locating Roots of Equations | ||
fcn_roots.m | Roots of functions or polynomials (invoking G.m) | |
poly_roots1.m | Roots of a cubic polynomial | |
newton_sys.m | Example of Newton's method for solving a nonlinear system | |
gauss_newton.m | Newton's method for solving nonlinear systems (invoking Fcn.m) | |
fractal.m | Fractal basins of attraction (CPb. 3.2.27) | |
poly_roots2.m | Roots of a fifth degree polynomial | |
Chapter 4: Interpolation and Numerical Differentiation | ||
newtn_int_poly.m | Newton interpolation polynomial equidistant pts | |
inverse_interp.m | Inverse Newton interpolation polynomial example | |
runge_fcn.m | Polynomial interpolation for the Runge function | |
Chapter 5: Numerical Integration | ||
num_int1.m | Numerical integration of exp(-x*x) (invoking f1.m) | |
num_int2.m | Numerical integration of sin(x)/x (invoking f2.m) | |
Chapter 6: More on Numerical Integration | ||
num_int3.m | Numerical intergratin of cos(2*x)/exp(x) (invoking f3.m) | |
cpb6_2_8.m | Computer Problem 6.2.8: Numerical intergration example | |
cpb6_2_9.m | Computer Problem 6.2.9: Difficult Numerical intergration | |
Chapter 7: Systems of Linear Equations | ||
gauss_elim1.m | Gaussian elimination to solve linear systems | |
gauss_elim2.m | Gaussian elimination to solve linear systems | |
Chapter 8: More on Systems of Linear Equations | ||
ldl.m | LDL Factorization | |
lu_fact.m | LU Factorization | |
eig.m | Eigenvalue Example | |
null.m | Null Space Example | |
timing.m | Timing eigenvalue computation | |
sng_val_decomp.m | Singular value decompositon of a matrix | |
cpb8_3_1d.m | Computer Problem 8.3.1d | |
mod_power.m | Modified Power Method | |
small_eig.m | Small eigenvalue | |
inv_power.m | Inverse Power Methods | |
shift_inv_power.m | Shifted Inverse Power Mehtod | |
Chapter 9: Approximation by Spline Functions | ||
spline_sin_plot.m | Plot of a cubic spline curve for sin(x) | |
spline_plot.m | Plot of a cubic spline curve | |
Chapter 10: Ordinary Differential Equations | ||
euler.m | Euler's method for solving an ODE (invoking f.m) | |
rk_ode23.m | Runge-Kutta method for solving an IVP (invoking ode23file1.m) | |
rkf_ode45.m | Runge-Kutta Fehlberg method for solving an IVP (invoking ode45file1.m) | |
Chapter 11: Systems of Ordinary Differential Equations | ||
rk2_ode23.m | Runge-Kutta method for systems of ODEs (invoking ode23file2.m) | |
rkf2_ode45.m | Runge-Kutta-Fehlberg method for systems of ODEs (invoking ode45file2.m) | |
Chapter 12: Smoothing of Data and the Method of Least Squares | ||
ls_fit.m | Linear least squares fit for polynomials | |
np_ls_fit.m | Least squares fit for a non-polynomial function | |
p_inv1.m | Minimal solution using pseudoin of matrices | |
p_inv2.m | Find pseudoinverse in case of loss in rank | |
Chapter 13: Monte Carlo Methods and Simulation | ||
rand.m | Examples using random numbers | |
Chapter 14: Boundary Value Problems for Ordinary Differential Equations | ||
bvp.m | Two-point boundary-value problem example (invoking bvpfcn.m, bvpbc.m) | |
Chapter 15: Partial Differential Equations | ||
heat.m | Heat Equation (invoking pdexlpde.m, pdexlic.m, pdexlbc.m) | |
par.m | Parabolic Equation (PDEdemo5) | |
wave.m | Wave Equation (PDEdemo6) | |
poisson.m | Poisson Equation (PDEdemo1) | |
fast.m | Fast Equation (PDEdemo8) | |
helm.m | Helmholtz Equation (PDEdemo2) | |
Chapter 16: Minimization of Functions | ||
fmin1.m | Minimizing multivariate functions | |
fmin2.m | Find local minimum of a function | |
Chapter 17: Linear Programming | ||
lin_prog1.m | Maximize subject to inequality constraints | |
lin_prog2.m | Minimize subject to inequality constraints | |
lin_prog3.m | Minimize subject to equality constraints | |
lin_prog4.m | Minimize subject to inequality constraints |
Addditional programs can be found at the textbook's anonymous ftp site:
ftp://ftp.ma.utexas.edu/pub/cheney-kincaid/
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