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Richardson ExtrapolationIn numerical analysis, Richardson extrapolation is a method to improve an approximation that depends on a step size. Let A(h) be an approximation of A that depends on a positive step size h with an error formula of the form -
where the ai are unknown constants and the ki are known constants such that hki > hki+1. The exact value sought can be given by -
which can be simplified with Big O notation to be -
Using the step sizes h and h / t for some t, the two formulas for A are: -
-
Multiplying the second equation by tk0 and subtracting the first equation gives -
which can be solved for A to give -
By this process, we have achieved a better approximation of A by subtracting the largest term in the error which was O(hk0). This process can be repeated to remove more error terms to get even better approximations. A general recurrence relation can be defined for the approximations by -
such that -
A well-known practical use of Richardson extrapolation is Romberg integration, which applies Richardson extrapolation to the trapezium rule. Example Using Taylor's theorem, -
so the derivative of f(x) is given by -
If the initial approximations of the derivative are chosen to be -
then ki = i+1. For t = 2, the first formula extrapolated for A would be -
For the new approximation -
we can extrapolate again to obtain -
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