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The error of the approximation is controllable.
By increasing the number of collocation points, the error of the approximation solution decreases rapidly.
Furthermore, we compute the error of the approximation by using the modulus of continuity and Lipschitz-type functionals.
The error of the approximation (tilde{f}(t)) of (f(t)) therefore decays like (2^{-(m+1)(k-1)}).
The parameters can be determined adaptively by minimizing a functional which measures the error of the approximation.
The use of the least squares method is also applied to minimize the error of the approximation function.
Similar(43)
In Table 1, we give the errors of the approximation of (B_{n,lambda}(f;x)) to (f(x)).
The lengths of these intervals are chosen according to several basic ideas that include an a priori estimate of the error of the Galerkin approximation.
Several approaches have been used to further minimize the error of the saddlepoint approximation [5].
(3.25) In this case we lose ({bar{N}}^{frac{1}{2}}) on the error of the best approximation of u by elements of the space (V_{delta}).
In this section, an upper bound for the error of the presented approximation scheme, with equidistant nodes, is obtained with a similar procedure as in [5].
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