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- W1501689968 abstract "There are several clustering and classification techniques developed within the last forty years. In recent analysis of EEG and MEG, common spatial patterns (CSP), support vector machines (SVMs), and k–mean are used more often. SVM has been applied to EEG signals for the removal of the eye–blinking artefact, detection of epileptic seizures, detection of evoked potentials (EPs), classification of left and right finger movement in BCI, and many other issues related to EEGs. CSP is generally used for feature detection of two classes. The features can then be classified or clustered using linear discriminant analysis (LDA), SVM or other classifiers. For detection of the movement–related EEG/MEG patterns, however, the CSP method and its variants show a very good performance in feature selection and classification for BCI purposes. Controlled Vocabulary Terms electroencephalography; magnetoencephalography" @default.
- W1501689968 created "2016-06-24" @default.
- W1501689968 creator A5004587843 @default.
- W1501689968 date "2013-05-24" @default.
- W1501689968 modified "2023-09-26" @default.
- W1501689968 title "Classification and Clustering of Brain Signals" @default.
- W1501689968 cites W2156909104 @default.
- W1501689968 doi "https://doi.org/10.1002/9781118622162.ch6" @default.
- W1501689968 hasPublicationYear "2013" @default.
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