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A SVD-BASED ALGORITHM FOR DENSE NONUNIFORM FAST FOURIER TRANSFORM

机译:一种基于SVD的密集非均匀傅立叶变换算法

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This work introduces a fast algorithm based on Singular Value Decomposition to compute the Nonuniform Fourier Transform. This approach is compared to proven techniques like the ones based on interpolation and least square approximation. Nonuniform Fourier exponentials are approximated through a set of optimum spaces obtained by modulating a single space. For a fixed precision, the space dimension is smaller with respect to the previous approaches, resulting in a computational cost reduction. Furthermore, the proposed formulation involves only real-complex multiplications rather than complex-complex ones. As a counterpart, the amount of projections to be computed is higher with respect to proven approaches. So, the proposed algorithm results to be optimum for dense nonuniformly sampled frequencies.
机译:这项工作引入了一种基于奇异值分解的快速算法来计算非均匀傅里叶变换。将这种方法与基于插值和最小二乘近似的验证技术进行比较。不均匀的傅里叶指数近似通过通过调制单个空间获得的一组最佳空间。为了固定精度,相对于先前的方法,空间尺寸较小,导致计算成本降低。此外,所提出的制剂仅涉及真实复杂的乘法而不是复杂复杂的。作为对应物,相对于经过验证的方法更高,计算的投影量更高。因此,所提出的算法导致密集的非均匀采样频率最佳。

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