John Travis
Mississippi College
Random lecture demonstrations dealing with numerical Integration.
Starting with Newton-Coates formulas...
For numerical integration, one can create approximations to integrals (and derivatives) by simply taking the integrand and approximating it with a polynomial (such as Lagrange) and then integrating the interpolating polynomial exactly...since it is only just a polynomial.
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Consider the Composite Trapezoidal Rule
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For Simpson's rule, approximate the actual integrand with a quadratic evaluated at equally spaced values from a to b and integrate that quadratic exactly. Notice, this will only require that the integrand be evaluated at three pionts over the interval.
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So, this suggests "Simpson's Rule"
$\int_a^b f(x) dx \approx (b-a)\left [ \frac{1}{6}f(a) + \frac{4}{6}f(\frac{a+b}{2}) + \frac{1}{6}f(b) \right ]$
1.70710678118655
1.72890675970461
1.70710678118655
1.72890675970461 |
What about using a cubic to approximate.....giving "Simpson's 3/8 Rule"
The following needs to be edited...
$\int_a^b f(x) dx \approx (b-a)\left [ \frac{1}{6}f(a) + \frac{4}{6}f(\frac{a+b}{2}) + \frac{1}{6}f(b) \right ]$
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This suggests "Simpson's 3/8 Rule"
$\int_a^b f(x) dx \approx (b-a)\left [ \frac{1}{8}f(a) + \frac{3}{8}f(a + \frac{b-a}{3}) + \frac{3}{8}f(a + 2\frac{b-a}{3}) + \frac{1}{8}f(b) \right ]$
1.70710678118655
1.71661348472682
1.70710678118655
1.71661348472682 |
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Since each of these formulas are scaled by the interval width b-a and only use a few points on that interval then if the interval is long then the approximations might be less accurate. Breaking up a larger interval therefore into pieces and reusing each formula over and over on the smaller pieces might be advantageous. Adding up the bits give the final result.
1.12176568093317
1.12176568093317
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Let's consider Gaussian Quadrature
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