Nonnegative tensor factorization for continuous EEG classification
SCIE
SCOPUS
- Title
- Nonnegative tensor factorization for continuous EEG classification
- Authors
- Lee, H; Kim, YD; Cichocki, A; Choi, S
- Date Issued
- 2007-08
- Publisher
- WORLD SCIENTIFIC PUBL CO PTE LTD
- Abstract
- In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classify multiple mental tasks. This is an extension of our previous work on the use of nonnegative matrix factorization (NMF) for EEG classification. Numerical experiments with two data sets in BCI competition, confirm the useful behavior of the method for continuous EEG classification.
- Keywords
- brian computer interface; EEG classification; nonnegative matrix factorization; nonnegative; tensor factorization; spectral feature extraction; COMMUNICATION
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/23202
- DOI
- 10.1142/S0129065707001159
- ISSN
- 0129-0657
- Article Type
- Article
- Citation
- INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, vol. 17, no. 4, page. 305 - 317, 2007-08
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