In various disciplines, information about the same phenomenon can be acquired from
different types of detectors, at different conditions, in multiple experiments or subjects …

Electroencephalography (EEG) is one fundamental tool for functional brain imaging. EEG
signals tend to be represented by a vector or a matrix to facilitate data processing and …

The widespread use of multisensor technology and the emergence of big data sets have
highlighted the limitations of standard flat-view matrix models and the necessity to move …

Tensor networks have in recent years emerged as the powerful tools for solving the large-
scale optimization problems. One of the most popular tensor network is tensor train (TT) …

Analysis and processing of very large data sets, or big data, poses a significant challenge.
Massive data sets are collected and studied in numerous domains, from engineering …

Vagus nerve stimulation (VNS) is widely used to treat drug-resistant epilepsy and
depression. While the precise mechanisms mediating its long-term therapeutic effects are …

Operations with tensors, or multiway arrays, have become increasingly prevalent in recent
years. Traditionally, tensors are represented or decomposed as a sum of rank-1 outer …

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

According to predictive-coding theory, cortical areas continuously generate and update
predictions of sensory inputs at different hierarchical levels and emit prediction errors when …

The problem of incomplete data–ie, data with missing or unknown values–in multi-way
arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometrics …