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).
Usage
hosvd(tnsr, ranks = NULL)
Arguments
tnsr
Tensor with K modes
ranks
a vector of desired modes in the output core tensor, default is tnsr@modes
Value
a list containing the following:
Z
core tensor with modes speficied by ranks
U
a list of orthogonal matrices, one for each mode
est
estimate of tnsr after compression
fnorm_resid
the Frobenius norm of the error fnorm(est-tnsr) - if there was no truncation, then this is on the order of mach_eps * fnorm.
Details
A progress bar is included to help monitor operations on large tensors.
References
L. Lathauwer, B.Moor, J. Vanderwalle "A multilinear singular value decomposition". Journal of Matrix Analysis and Applications 2000.