Higher-order SVD of a K-Tensor. Write the K-Tensor as a (m-mode) product of a core Tensor (possibly smaller modes) and K orthogonal factor matrices. Truncations can be specified via
ranks (making them smaller than the original modes of the K-Tensor will result in a truncation). For the mathematical details on HOSVD, consult Lathauwer et. al. (2000).
Tensor with K modes
a vector of desired modes in the output core tensor, default is
A progress bar is included to help monitor operations on large tensors.
a list containing the following:
core tensor with modes speficied by
a list of orthogonal matrices, one for each mode
tnsr after compression
the Frobenius norm of the error
fnorm(est-tnsr) - if there was no truncation, then this is on the order of mach_eps * fnorm.
The length of
ranks must match
L. Lathauwer, B.Moor, J. Vanderwalle "A multilinear singular value decomposition". Journal of Matrix Analysis and Applications 2000.
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