atkinson
atkinson,
a MATLAB code which
contains examples from Atkinson's textbook "Elementary Numerical Analysis".
Languages:
atkinson is available in
a FORTRAN77 version and
a MATLAB version.
Related:
atkinson_test
cheney_kincaid,
a MATLAB code which
contains examples from Cheney and Kincaid's
Numerical Mathematics and Computing text.
conte_deboor,
a MATLAB code which
contains examples from Conte and deBoor's Elementary Numerical Analysis text.
Author:
Original MATLAB version by Kendall Atkinson and Weimin Han.
Reference:
-
Kendall Atkinson, Weimin Han,
Elementary Numerical Analysis,
Wiley, 2004,
ISBN: 0471433373,
LC: QA297.A83.2004.
Source Code:
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ab2.m,
use an Adams-Bashforth formula to solve a differential equation.
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bisect.m,
use bisection to solve a nonlinear equation.
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deriv.m,
evaluates the derivative for the direction field computation.
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dirfield.m,
plots the direction field of y' = f(x,y).
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divdif.m,
calculates a divided difference table.
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euler_back.m,
uses the backward Euler method to solve an
initial value problem.
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euler_for.m,
uses the forward Euler method to solve an
initial value problem.
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eulersys.m,
uses Euler's method to solve a system of initial value problems.
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eval_exp_simple.m,
evaluates several Taylor polynomials of increasing degree.
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eval_exp_tay.m,
evaluates several Taylor polynomials of increasing degree.
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exp_tay.m,
produces the Taylor coefficients for exp(x) around x=0.
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gaussint.m,
estimates an integral using an n-point Gauss rule.
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gepivot.m,
solves a system of linear equations using Gauss
elimination with partial pivoting.
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gs.m,
uses the Gauss-Seidel iterative method to solve
a system of linear equations.
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heat1.m,
uses the forward difference method to solve the
initial boundary value problem of the heat equation.
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heat2.m,
uses the backward difference method to solve the
initial boundary value problem of the heat equation.
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humps_fun.m,
evaluates the humps function, used for certain demonstrations.
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interp.m,
evaluates an interpolant based on a divided difference table.
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jacobi.m,
uses the Jacobi iterative method to solve
a system of linear equations.
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log_tay.m,
produces the Taylor coefficents of log(x) around x=1.
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ncs.m,
compute the natural cubic spline interpolant to data.
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newton.m,
uses Newton's method to solve a nonlinear equation.
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newton_sys.m,
uses Newton's method to solve a system of nonlinear equations.
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odebvp.m,
solves a two-point boundary value problem.
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plot_exp.m,
plots several Taylor polynomials for exp(x).
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plot_log.m,
plots several Taylor polynomials for log(x).
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plot_sin.m
plots several Taylor polynomials for sin(x).
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plot_sint.m,
plots several Taylor polynomials for the sine integral function.
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poisson.m,
solves the Poisson problem on the unit square.
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polyeval.m,
evaluates a Taylor polynomial.
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poly_even.m,
evaluates an even Taylor polynomial.
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poly_odd.m,
evaluates an odd Taylor polynomial.
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power_method.m,
uses the power method to find the eigenvalue of
largest magnitude associated with a matrix.
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secant.m,
uses the secant method to solve a nonlinear equation.
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simpson.m,
uses Simpson's rule to estimate the integral of a function.
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sin_tay.m,
evaluates the coefficients of the Taylor approximation
to the sine function.
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sint.m,
evaluates an approximation to the sine integral function.
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sint_tay.m,
evaluates the coefficients of the Taylor approximation
to the sine integral function.
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taylor_3d.m,
plots a 3D graph of variation in a Taylor approximation
for log(x) of increasing degree.
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trapezoidal.m,
uses the trapezoidal rule to estimate an integral.
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trapezoidal_ode.m,
uses the trapezoidal rule to solve an initial value problem.
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tridiag.m,
solves a tridiagonal system of linear equations.
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wave.m,
uses centered differences to solve the initial-boundary value problem
for the wave equation.
Last revised on 17 August 2022.