Multilinear generalization of common spatial pattern

Qibin Zhao, Liqing Zhang, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Citations (Scopus)

Abstract

The Common Spatial Patterns (CSP) algorithm has been widely used in EEG classification and Brain Computer Interface (BCI). In this paper, we propose a multilinear formulation of the CSP, termed as TensorCSP or Common Tensor Discriminant Analysis (CTDA) for high-order tensor data. As a natural extension of CSP, the proposed algorithm uses the analogous optimization criteria in CSP and a new framework for simultaneous optimization of projection matrices on each mode based on tensor analysis theory is developed. Experimental results demonstrate that our proposed algorithm is able to improve classification accuracy of multi-class motor imagery EEG.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages525-528
Number of pages4
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: 19 Apr 200924 Apr 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/TerritoryTaiwan, Province of China
CityTaipei
Period19/04/0924/04/09

Keywords

  • Brain computer interface
  • Common spatial pattern
  • EEG
  • Tensor

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