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Fast PCA via UTV decomposition and application on EEG analysis

  • Yodchanan Wongsawat

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

5 Citations (Scopus)

Abstract

In the mean square error sense, principal component analysis (PCA) or Karhunen-Loeve transform (KLT) can optimally summarize the high dimensional data into only a few meaningful ones. However, for the biomedical signal analysis, e.g. electroencephalogram (EEG), the data need to be updated or downdated very often. This fact makes the PCA impractical to be employed, especially in real-time signal analysis. In this paper, we propose the fast computational method for approximating the PCA such that the new transform, called fast PCA (fastPCA), can easily be updated and downdated. The fastPCA is calculated via the UTV decomposition which is the method normally used to approximate the rank-revealing property of the singular value decomposition (SVD). The merit of the fastPCA is also illustrated via the application on EEG analysis.

Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages5669-5672
Number of pages4
ISBN (Print)9781424432967
DOIs
Publication statusPublished - 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2 Sept 20096 Sept 2009

Publication series

NameProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period2/09/096/09/09

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