Approximation of functions on the sphere on a Sobolev space with a Gaussian measure in the probabilistic case setting

Approximation of functions on the sphere on a Sobolev space with a Gaussian measure in the probabilistic case setting
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在概率案例设置中用高斯测度逼近 Sobolev 空间上的球体函数

DOI:
10.1142/s0219691314610128
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发表时间:
2014-09
期刊:
International Journal of Wavelets, Multiresolution and Information Processing
影响因子:
--
通讯作者:
Zhai, Xuebo
Zhai, Xuebo
中科院分区:
其他
文献类型:
--
作者:
Wang, Heping;Zhai, Xuebo

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本文在概率情形下,讨论了球面上函数在具有Gauss测度的Sobolev空间上的最佳球面多项式逼近,以及Fourier部分和算子和Vallee-Poussin算子的逼近,并得到了概率误差估计.证明了在概率情形下,当1 ≤ q ≤ ∞时,Fourier部分和算子和Vallee-Poussin算子是Lq空间中的阶最优线性算子,而当2 < q ≤ ∞时,球面多项式空间不是Lq空间中的阶最优线性算子.这与平均情况下的情况完全不同,平均情况下,当1 ≤ q < ∞时,球面多项式空间在Lq空间中是阶最优的。此外,在Lq空间(1 ≤ q ≤ ∞)中,最坏情况的序最优子空间在概率情况下也是序最优的。
In this paper, we discuss the best approximation of functions on the sphere by spherical polynomials and the approximation by the Fourier partial summation operators and the Vallee-Poussin operators, on a Sobolev space with a Gaussian measure in the probabilistic case setting, and get the probabilistic error estimation. We show that in the probabilistic case setting, the Fourier partial summation operators and the Vallee-Poussin operators are the order optimal linear operators in the Lq space for 1 ≤ q ≤ ∞, but the spherical polynomial spaces are not order optimal in the Lq space for 2 < q ≤ ∞. This is completely different from the situation in the average case setting, which the spherical polynomial spaces are order optimal in the Lq space for 1 ≤ q < ∞. Also, in the Lq space for 1 ≤ q ≤ ∞, worst-case order optimal subspaces are also order optimal in the probabilistic case setting.
平均情况设置下球体上 Sobolev 空间上的函数逼近
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