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 …

Multidimensional NMR spectroscopy has been established as an indispensible tool for
studying structure, dynamics, and interactions of biopolymers. When used in the frame of a …

With the increasing availability of various sensor technologies, we now have access to large
amounts of multiblock (also called multiset, multirelational, or multiview) data that need to be …

Data analysis has wide applications in eliminating the irrelevant and redundant components
in signals to reveal the important informational characteristics that are required …

The localization of brain sources based on EEG measurements is a topic that has attracted a
lot of attention in the last decades and many different source localization algorithms have …

We discuss a technique that allows blind recovery of signals or blind identification of
mixtures in instances where such recovery or identification were previously thought to be …

Neuronal power attenuation or enhancement in specific frequency bands over the
sensorimotor cortex, called Event-Related Desynchronization (ERD) or Event-Related …

In this paper, we propose a framework to compute approximate CANDECOMP/PARAFAC
(CP) decompositions. Such tensor decompositions are viable tools in a broad range of …

Multi-dimensional model order selection (MOS) techniques achieve an improved accuracy,
reliability, and robustness, since they consider all dimensions jointly during the estimation of …

Objective: Multivariate signal (MS) analysis, especially the assessment of its information
transmission (for example, from the perspective of network science), is the key to our …