Single- and multi-variate tensor spectral analysis

摘要

Tensor analysis includes: obtaining a set of Fourier domain singular value decomposition (SVD) factors of a first tensor representing data in multiple dimensions, including: performing Fourier transform on the first tensor along a first dimension to obtain a Fourier domain tensor; performing SVD on the Fourier domain tensor to obtain a first set of Fourier domain SVD tensors; performing inverse Fourier transform on at least some of the first set of Fourier domain SVD tensors to obtain a set of native domain tensors; performing Fourier transform on at least some of the set of native domain tensors to obtain a second set of Fourier domain tensors; performing SVD on at least some of the second set of Fourier domain tensors to obtain a second set of Fourier domain SVD tensors; obtaining an SVD result based at least in part on the set of Fourier domain SVD factors of the first tensor; and outputting at least a portion of the SVD result.