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 …

This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from
electroencephalograms (EEG). Three major effects of AD on EEG have been observed …

Modern applications in engineering and data science are increasingly based on
multidimensional data of exceedingly high volume, variety, and structural richness …

Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part
because the clinical diagnosis of major depression encompasses biologically …

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 …

Signal processing is the key component of any vibration-based structural health monitoring
(SHM). The goal of signal processing is to extract subtle changes in the vibration signals in …

Independent component analysis (ICA) and blind source separation (BSS) methods are
increasingly used to separate individual brain and non-brain source signals mixed by …

Reservoirs are fundamental human‐built infrastructures that collect, store, and deliver fresh
surface water in a timely manner for many purposes. Efficient reservoir operation requires …

A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach
consists of sifting an ensemble of white noise-added signal (data) and treats the mean as …

This is the first comprehensive book on information geometry, written by the founder of the
field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide …