[Eeglablist] Tensor Decomposition of EEG Signals

CONG Fengyu 丛丰裕 fengyu.cong at aliyun.com
Fri May 29 15:55:22 PDT 2015

Dear EEGLablist members,I would like to introduce my new review
paper to you. It is about Tensor Decomposition of EEG Signals and published in Journal
of Neuroscience Methods. The paper is open access and can be downloaded via http://www.sciencedirect.com/science/article/pii/S0165027015001016.
The demo of MATLAB codes and ERP data can be downloaded via http://www.escience.cn/people/cong/AdvancedSP_ERP.html
EEG signals tend to be represented by a
vector or a matrix to facilitate data processing and analysis with generally
understood methodologies like time-series analysis, spectral analysis and
matrix decomposition. Indeed, EEG signals are often naturally
born with more than two modes of time and space, and they can be denoted by a
multi-way array called as tensor. This review summarizes the current progress
of tensor decomposition of EEG signals with three aspects. The first is about the
existing modes and tensors of EEG signals. Second, two fundamental tensor
decomposition models, canonical polyadic decomposition (CPD, it is also called
parallel factor analysis-PARAFAC) and Tucker decomposition, are introduced and
compared. Moreover, the applications of the two models for EEG signals are
addressed. Particularly, the determination of the number of components for each
mode is discussed. Finally, the N-way partial least square and higher-order
partial least square are described for a potential trend to process and analyze
brain signals of two modalities simultaneously.Looking forward to your comments and
suggestions on tensor decomposition of EEG signals. Sincerely, Fengyu P.S.: The bibliography of the paper is as
the following: Fengyu Cong, Qiu-Hua Lin, Li-Dan Kuang,
Xiao-Feng Gong, Piia Astikainen, Tapani Ristaniemi, Tensor Decomposition of EEG
Signals: A Brief Review, Journal of Neuroscience Methods 248: 59–69, 2015.
--Fengyu Cong, Ph.D., IEEE Senior Member
Professor, Department of Biomedical Engineering, Dalian University of Technology, China
Docent (Adjunct Associate Professor), University of Jyvaskyla, Finland
Email: cong at dlut.edu.cn, fengyu.cong at aliyun.com
Homepage: http://www.escience.cn/people/cong/index.html

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