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Multivariate sparse FFT based on rank-1 Chebyshev lattice sampling

机译:基于Rank-1 Chebyshev格式采样的多变量稀疏FFT

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We present a method for the fast reconstruction of high-dimensional sparse algebraic polynomials in Chebyshev form and for the fast approximation of multivariate non-periodic functions from samples, when the frequency locations belonging to the non-zero or largest Chebyshev coefficients are unknown. We only assume that we have given a generally very large index set of possible frequencies, e.g. a d-dimensional full grid. We determine the frequency locations in a dimension-incremental way from samples along reconstructing rank-1 Chebyshev lattices. We demonstrate the high performance of the proposed method in numerical examples in up to 15 dimensions.
机译:我们介绍了一种方法,用于在Chebyshev形式中快速重建高维稀疏代数多项式,并且当属于非零或最大的Chebyshev系数的频率位置未知时,来自样本的多变量非周期性功能的快速近似。我们只假设我们已经给出了一般非常大的可能频率的指标集,例如, D维全网格。我们以重建Rank-1 Chebyshev格子的样本中的维度增量方式确定频率位置。我们在最多15维度的数值例子中展示了所提出的方法的高性能。

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