Description Usage Arguments Value Author(s) References Examples
TTSVD incrementaly decomposes the input tensor by singular value decomposition (SVD).
1 |
A |
The input tensor. |
Ranks |
TT-ranks to specify the lower dimensions. |
accuracy |
The accuracy of the compression. |
G : Core tensors
Koki Tsuyuzaki
I. V. Oseledets, (2011). Tensor-Train Decomposition. SIAM J. SCI. COMPUT.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | library("rTensor")
# Tensor data
X1 <- array(rnorm(3*5*7*9*11), c(3,5,7,9,11))
dimnames(X1) <- list(
I=paste0("i", 1:3),
J=paste0("j", 1:5),
K=paste0("k", 1:7),
L=paste0("l", 1:9),
M=paste0("m", 1:11)
)
X1 <- as.tensor(X1)
# TT-ranks
Ranks <- c(p=2, q=4, r=6, s=8)
# TTSVD
out.TTSVD <- TTSVD(X1, Ranks)
out.TTSVD <- TTSVD(X1, accuracy=1E-10)
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