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Exponentially accurate Runge-free approximation of non-periodic functions from samples on an evenly spaced grid

机译:均匀间隔网格上样本的非周期性函数的指数精确的无Runge逼近

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Approximating a function from its values f(xi) at a set of evenly spaced points xi through (N+1)-point polynomial interpolation often fails because of divergence near the endpoints, the “Runge Phenomenon”. This report shows how to achieve an error that decreases exponentially fast with N. Normalizing the span of the points to [?1,1], the new strategy applies a filtered trigonometric interpolant on the subinterval x[?1+D,1?D] and ordinary polynomial interpolation in the two remaining subintervals. Convergence is guaranteed because the width D of the polynomial interpolation subintervals decreases as N→∞, being proportional to . Applications to the Gibbs Phenomenon and hydrodynamic shocks are discussed.
机译:在一组均匀间隔的点xi到(N + 1)点多项式插值中,从函数值f(xi)近似函数通常会因端点附近的发散(“ Runge现象”)而失败。该报告显示了如何实现随N呈指数下降的误差。将点的跨度归一化为[?1,1],新策略将滤波后的三角插值应用于子区间x [?1 + D,1?D ]和普通的多项式插值在剩余的两个子区间中。由于多项式插值子间隔的宽度D随着N→∞的减小而减小,与N成正比,因此可以保证收敛。讨论了吉布斯现象和流体动力学冲击的应用。

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