During the last years, low‐rank tensor approximation has been established as a new tool in
scientific computing to address large‐scale linear and multilinear algebra problems, which …

Tensors or multiway arrays are functions of three or more indices (i, j, k,...)-similar to matrices
(two-way arrays), which are functions of two indices (r, c) for (row, column). Tensors have a …

This survey provides an overview of higher-order tensor decompositions, their applications,
and available software. A tensor is a multidimensional or-way array. Decompositions of …

Near-infrared spectroscopy (NIRS) is a fast and powerful analytical tool in the food industry.
As an advanced chemometrics tool, multi-way analysis shows great potential for solving a …

The CANDECOMP/PARAFAC (CP) decomposition is a leading method for the analysis of
multiway data. The standard alternating least squares algorithm for the CP decomposition …

Tensor decompositions are at the core of many blind source separation (BSS) algorithms,
either explicitly or implicitly. In particular, the canonical polyadic (CP) tensor decomposition …

We define the hierarchical singular value decomposition (SVD) for tensors of order d\geq2.
This hierarchical SVD has properties like the matrix SVD (and collapses to the SVD in d=2) …

This work was originally motivated by a classification of tensors proposed by Richard
Harshman. In particular, we focus on simple and multiple 'bottlenecks', and on 'swamps' …

The canonical polyadic and rank-(L_r,L_r,1) block term decomposition (CPD and BTD,
respectively) are two closely related tensor decompositions. The CPD and, recently, BTD are …

Detection and estimation problems in multiple-input multiple-output (MIMO) radar have
recently drawn considerable interest in the signal processing community. Radar has long …