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- Title
NONNEGATIVE TENSOR FACTORIZATION FOR CONTINUOUS EEG CLASSIFICATION.
- Authors
LEE, HYEKYOUNG; KIM, YONG-DEOK; CICHOCKI, ANDRZEJ; CHOI, SEUNGJIN
- 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.
- Subjects
ELECTROENCEPHALOGRAPHY; FACTORIZATION; CALCULUS of tensors; ALGORITHM research; BRAIN-computer interfaces; ARTIFICIAL neural networks
- Publication
International Journal of Neural Systems, 2007, Vol 17, Issue 4, p305
- ISSN
0129-0657
- Publication type
Article
- DOI
10.1142/S0129065707001159