t_svd_reconstruct

Reconstruct the original 3-Tensor after it has been decomposed into <code>U, S, V</code> via <code>t_svd</code>.

A set of tools for creation, manipulation, and modeling
of tensors with arbitrary number of modes. A tensor in the context of data
analysis is a multidimensional array. rTensor does this by providing a S4
class 'Tensor' that wraps around the base 'array' class. rTensor
provides common tensor operations as methods, including matrix unfolding,
summing/averaging across modes, calculating the Frobenius norm, and taking
the inner product between two tensors. Familiar array operations are
overloaded, such as index subsetting via '[' and element-wise operations.
rTensor also implements various tensor decomposition, including CP, GLRAM,
MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements
transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some
auxiliary functions include the Khatri-Rao product, Kronecker product, and
the Hadamard product for a list of matrices.

Koki Tsuyuzaki

rTensor

Tools for Tensor Analysis and Decomposition

James Li

Jacob Bien

Martin Wells

t_svd_reconstruct function

<dl><dt>L</dt>
<dd>list that is an output from <code>t_svd</code></dd></dl>

Arguments

Reconstruct Tensor From TSVD — t_svd_reconstruct

<dl>

<dt>L</dt>
<dd>list that is an output from <code>t_svd</code></dd>

</dl>

t_svd_reconstruct: Reconstruct Tensor From TSVD

Description

Usage

Value

Arguments

See Also

Examples