TTSVD: Tensor-Train Decomposition by TTSVD

In rikenbit/ttTensor: Tensor-Train Decomposition

Tensor-Train Decomposition by TTSVD

Description

TTSVD incrementaly decomposes the input tensor by singular value decomposition (SVD).

Usage

TTSVD(A, Ranks=NULL, accuracy=NULL)

Arguments

A	The input tensor.
Ranks	TT-ranks to specify the lower dimensions.
accuracy	The accuracy of the compression.

Value

G : Core tensors

Author(s)

Koki Tsuyuzaki

References

I. V. Oseledets, (2011). Tensor-Train Decomposition. SIAM J. SCI. COMPUT.

Examples

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)

rikenbit/ttTensor documentation built on Feb. 2, 2023, 4:32 a.m.