Difference between revisions of "Method of undetermined coefficients in developing numerical algorithms"
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A special method for constructing algorithms based on the requirement that the algorithms should be exact or have an error of prescribed order of accuracy on some set of problems. | A special method for constructing algorithms based on the requirement that the algorithms should be exact or have an error of prescribed order of accuracy on some set of problems. | ||
− | A typical example of problems that can be solved by the method of undetermined coefficients is the following (see [[#References|[1]]], [[#References|[2]]]). (It can also be solved by other methods.) Let the values | + | A typical example of problems that can be solved by the method of undetermined coefficients is the following (see [[#References|[1]]], [[#References|[2]]]). (It can also be solved by other methods.) Let the values $f(P_1),\ldots,f(P_n)$ of a function be known. It is required to construct a formula for the approximation of the function |
− | + | $$f(P)\approx g(f(P_1),\ldots,f(P_N),P);$$ | |
to construct a formula for computing the derivative: | to construct a formula for computing the derivative: | ||
− | + | $$Df(P)\approx g_D(f(P_1),\ldots,f(P_N),P);$$ | |
and to construct a formula for computing the integral: | and to construct a formula for computing the integral: | ||
− | + | $$I(f)=\int\limits_\Omega f(P)p(P)dP\approx g_1(f(P_1),\ldots,f(P_n)).$$ | |
To solve the last of these problems one is given some form of an approximate solution, for example, linear: | To solve the last of these problems one is given some form of an approximate solution, for example, linear: | ||
− | + | $$g_1=\sum_{n=1}^NC_nf(P_n),$$ | |
− | and one determines the coefficients | + | and one determines the coefficients $C(f)$ from the requirement that the approximate formula $I(f)\approx g_1$ should be exact for functions of a certain collection; for example, for those of the form |
− | + | $$f(P)=\sum_{m=1}^Ma_m\omega_m(P),$$ | |
− | where the | + | where the $\omega_m(P)$ are fixed and the $a_m$ are arbitrary. As a rule one takes $M=N$. For the equality |
− | + | $$I\left(\sum_{m=1}^Ma_m\omega_m\right)=\sum_{n=1}^NC_n\left(\sum_{m=1}^Ma_m\omega_m(P_n)\right)$$ | |
− | to hold for all | + | to hold for all $a_m$ it suffices that |
− | + | $I(\omega_m)=\sum_{n=1}^NC_n\omega_n(P_n),\quad m=1,\ldots,M.$$ | |
− | From this one determines the | + | From this one determines the $C_n$ (if this is possible). |
Sometimes one is given a more complicated form of dependence. For example, frequently it is known that the function in question has a good approximation by functions of the form | Sometimes one is given a more complicated form of dependence. For example, frequently it is known that the function in question has a good approximation by functions of the form | ||
− | + | $$g(a_1,\ldots,a_M,P),$$ | |
− | where the | + | where the $a_m$ are known. The parameters $a_m$ are chosen from the system of equations |
− | + | $$g(a_1,\ldots,a_M,P_n)=f(P_n),\quad n=1,\ldots,N.$$ | |
In the case of formulas for numerical integration, often the coordinates of the nodes of integration stand out as unknown parameters. For example, in the [[Gauss quadrature formula|Gauss quadrature formula]] | In the case of formulas for numerical integration, often the coordinates of the nodes of integration stand out as unknown parameters. For example, in the [[Gauss quadrature formula|Gauss quadrature formula]] | ||
− | + | $$I(f)=\int_a^bf(x)p(x)dx\approx\sum_{n=1}^NC_nf(P_n)$$ | |
− | one considers as free parameters the coordinates of the nodes | + | one considers as free parameters the coordinates of the nodes $P_n$; owing to this one succeeds in constructing quadratures that are exact for polynomials of degree $2N-1$. In the construction of approximations of differential equations by the method of undetermined coefficients it is required that under substitution in a finite-difference scheme the solutions of the problem give compatible ([[Discrepancy|discrepancy]]) values of prescribed order of smallness in relation to the step of the grid. Such a device lies at the basis of ways for constructing Runge–Kutta methods and finite-difference methods (see [[#References|[1]]], [[#References|[2]]]). |
The method of undetermined coefficients is also used in constructing approximations of partial differential equations (see [[#References|[3]]]). | The method of undetermined coefficients is also used in constructing approximations of partial differential equations (see [[#References|[3]]]). |
Revision as of 11:56, 12 August 2014
A special method for constructing algorithms based on the requirement that the algorithms should be exact or have an error of prescribed order of accuracy on some set of problems.
A typical example of problems that can be solved by the method of undetermined coefficients is the following (see [1], [2]). (It can also be solved by other methods.) Let the values $f(P_1),\ldots,f(P_n)$ of a function be known. It is required to construct a formula for the approximation of the function
$$f(P)\approx g(f(P_1),\ldots,f(P_N),P);$$
to construct a formula for computing the derivative:
$$Df(P)\approx g_D(f(P_1),\ldots,f(P_N),P);$$
and to construct a formula for computing the integral:
$$I(f)=\int\limits_\Omega f(P)p(P)dP\approx g_1(f(P_1),\ldots,f(P_n)).$$
To solve the last of these problems one is given some form of an approximate solution, for example, linear:
$$g_1=\sum_{n=1}^NC_nf(P_n),$$
and one determines the coefficients $C(f)$ from the requirement that the approximate formula $I(f)\approx g_1$ should be exact for functions of a certain collection; for example, for those of the form
$$f(P)=\sum_{m=1}^Ma_m\omega_m(P),$$
where the $\omega_m(P)$ are fixed and the $a_m$ are arbitrary. As a rule one takes $M=N$. For the equality
$$I\left(\sum_{m=1}^Ma_m\omega_m\right)=\sum_{n=1}^NC_n\left(\sum_{m=1}^Ma_m\omega_m(P_n)\right)$$
to hold for all $a_m$ it suffices that
$I(\omega_m)=\sum_{n=1}^NC_n\omega_n(P_n),\quad m=1,\ldots,M.'"`UNIQ-MathJax7-QINU`"'g(a_1,\ldots,a_M,P),'"`UNIQ-MathJax8-QINU`"'g(a_1,\ldots,a_M,P_n)=f(P_n),\quad n=1,\ldots,N.'"`UNIQ-MathJax9-QINU`"'I(f)=\int_a^bf(x)p(x)dx\approx\sum_{n=1}^NC_nf(P_n)$$ one considers as free parameters the coordinates of the nodes $P_n$; owing to this one succeeds in constructing quadratures that are exact for polynomials of degree $2N-1$. In the construction of approximations of differential equations by the method of undetermined coefficients it is required that under substitution in a finite-difference scheme the solutions of the problem give compatible (discrepancy) values of prescribed order of smallness in relation to the step of the grid. Such a device lies at the basis of ways for constructing Runge–Kutta methods and finite-difference methods (see [1], [2]).
The method of undetermined coefficients is also used in constructing approximations of partial differential equations (see [3]).
References
[1] | I.S. Berezin, N.P. Zhidkov, "Computing methods" , Pergamon (1973) (Translated from Russian) |
[2] | N.S. Bakhvalov, "Numerical methods: analysis, algebra, ordinary differential equations" , MIR (1977) (Translated from Russian) |
[3] | S.K. Godunov, V.S. Ryaben'kii, "The theory of difference schemes" , North-Holland (1964) (Translated from Russian) |
Comments
The techniques of curve and surface fitting may be considered as a form of, what is here called, the method of undetermined coefficients.
Method of undetermined coefficients in developing numerical algorithms. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Method_of_undetermined_coefficients_in_developing_numerical_algorithms&oldid=13040