Ékstrapolasi Richardson: Béda antarrépisi
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Dina [[analisis numeris]], '''ékstrapolasi Richardson''' nyaéta métode [[akselerasi runtuyan]], nu digunakeun pikeun ngabebenah [[rarata konvergénsi]] tina [[runtuyan]]. Dingaranan sanggeus kapanggih ku [[Lewis Fry Richardson]], nu manggihan téhnik ieu dina mangsa awal [[abad ka-20]]. |
Dina [[analisis numeris]], '''ékstrapolasi Richardson''' nyaéta métode [[akselerasi runtuyan]], nu digunakeun pikeun ngabebenah [[rarata konvergénsi]] tina [[runtuyan]]. Dingaranan sanggeus kapanggih ku [[Lewis Fry Richardson]], nu manggihan téhnik ieu dina mangsa awal [[abad ka-20]]. |
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==Définisi basajan== |
== Définisi basajan == |
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{{tarjamahkeun|Inggris}} |
{{tarjamahkeun|Inggris}} |
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Suppose that ''A''(''h'') is an estimation of order ''h<sup>n</sup>'' for |
Suppose that ''A''(''h'') is an estimation of order ''h<sup>n</sup>'' for |
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than ''A(h')'' with a much smaller '' h' '', which can cause problems due to limited precision (rounding errors) and/or due to the increasing number of calculations needed (see examples below). |
than ''A(h')'' with a much smaller '' h' '', which can cause problems due to limited precision (rounding errors) and/or due to the increasing number of calculations needed (see examples below). |
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==Rumus umum== |
== Rumus umum == |
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Let ''A''(''h'') be an approximation of ''A'' that depends on a positive step size ''h'' with an [[Approximation error|error]] formula of the form |
Let ''A''(''h'') be an approximation of ''A'' that depends on a positive step size ''h'' with an [[Approximation error|error]] formula of the form |
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:<math> A - A(h) = a_0h^{k_0} + a_1h^{k_1} + a_2h^{k_2} + \cdots </math> |
:<math> A - A(h) = a_0h^{k_0} + a_1h^{k_1} + a_2h^{k_2} + \cdots </math> |
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It should be noted that the Richardson extrapolation can be considered as a linear [[sequence transformation]]. |
It should be noted that the Richardson extrapolation can be considered as a linear [[sequence transformation]]. |
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==Conto== |
== Conto == |
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Using [[Taylor's theorem]], |
Using [[Taylor's theorem]], |
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:<math> A = \frac{4A_1\left(\frac{h}{2}\right) - A_1(h)}{3} + O(h^3) .</math> |
:<math> A = \frac{4A_1\left(\frac{h}{2}\right) - A_1(h)}{3} + O(h^3) .</math> |
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==Rujukan== |
== Rujukan == |
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*''Extrapolation Methods. Theory and Practice'' ku C. Brezinski jeung M. Redivo Zaglia, North-Holland, 1991. |
*''Extrapolation Methods. Theory and Practice'' ku C. Brezinski jeung M. Redivo Zaglia, North-Holland, 1991. |
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==Tempo ogé== |
== Tempo ogé == |
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* [[Aitken's delta-squared process]] |
* [[Aitken's delta-squared process]] |
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* [http://www.google.com/search?q=Richardson+extrapolation Nyungsi 'Richardson extrapolation' di google] |
* [http://www.google.com/search?q=Richardson+extrapolation Nyungsi 'Richardson extrapolation' di google] |
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[[Kategori:Analisis numeris]] |
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[[Kategori:Analisis asimtotis]] |
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[[fr:Extrapolation de Richardson]] |
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[[sr:Ричардсонова екстраполација]] |
[[sr:Ричардсонова екстраполација]] |
Révisi nurutkeun 21 Juni 2009 01.37
Dina analisis numeris, ékstrapolasi Richardson nyaéta métode akselerasi runtuyan, nu digunakeun pikeun ngabebenah rarata konvergénsi tina runtuyan. Dingaranan sanggeus kapanggih ku Lewis Fry Richardson, nu manggihan téhnik ieu dina mangsa awal abad ka-20.
Définisi basajan
Artikel ieu keur dikeureuyeuh, ditarjamahkeun tina basa Inggris. Bantuanna didagoan pikeun narjamahkeun. |
Suppose that A(h) is an estimation of order hn for , i.e. . Then
is called the Richardson extrapolate of A(h); it is an estimate of order hm for A, with m>n.
More generally, the factor 2 can be replaced by any other factor, as shown below.
Very often, it is much easier to obtain a given precision by using R(h) rather than A(h') with a much smaller h' , which can cause problems due to limited precision (rounding errors) and/or due to the increasing number of calculations needed (see examples below).
Rumus umum
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.
It should be noted that the Richardson extrapolation can be considered as a linear sequence transformation.
Conto
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
Rujukan
- Extrapolation Methods. Theory and Practice ku C. Brezinski jeung M. Redivo Zaglia, North-Holland, 1991.