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Smoothing curve by orthogonal polynomials with non-differentiable functions as their weight functions

机译:通过具有非可微分功能的正交多项式平滑曲线作为其重量函数

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The interpolation by polynomial of degree n, p_n(x), may smooth any curve y = f (x) with the condition that this polynomial must passes through n +1 points of the curve y = f (x). This condition may prevent the curve of y = p_n(x) different from the exact curve of y = f (x) especially in the case that the points of f (x) are obtained from an experiment which may not be the exact point of the curve y = f (x). But the least square approximation by orthogonal polynomial q_n (x), may give the better shape than the interpolation by polynomial p_n(x). However the curve of y = q_n (x) may not pass through any exact point of the curve y = f (x). M.Podisuk, P.Rattanathanawan and P.Phataranavik, in [1], introduced the sequences of orthogonal polynomials with step functions as their weight functions but they did not use them for least square approximation. In this paper, the sequences of orthogonal polynomials with nondifferentiable functions as their weight functions will be used for least square approximation.
机译:通过多项式度n,P_N(X)的内插,可以平滑与此多项式必须穿过曲线y = F(x)的n个1点的情况的任何曲线y = F(X)。这个条件可以防止Y的= P_N(X)从y的准确曲线不同的曲线= F(x)的尤其是在F(X)的点是从实验中获得的情况下,这可能不是确切的点曲线y = F(X)。但通过正交多项式Q_N(x)的最小二乘逼近,可以给出比由多项式P_N(X)的内插的更好的形状。 Y的但是曲线= Q_N(x)可以不通过曲线y = F(X)的任何确切点。 M.Podisuk,P.Rattanathanawan和P.Phataranavik,在[1],引入的正交多项式与阶梯函数序列作为它们的重量的功能,但他们并没有使用它们进行最小二乘逼近。在本文中,与非可微函数作为他们的权重函数的正交多项式的序列将被用于最小二乘逼近。

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