A novel effective feature selection algorithm based on S-PCA and wavelet transform features in EEG signal classification

2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011

Volumn , Issue , 2011, Pages 114-117

  Nasehi, Saadat ^a   Pourghassem, Hossein ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

EEG signal; feature extraction; KNN classifier; Statistical Principal Component Analysis; wavelet transform

Indexed keywords

BRAIN ACTIVITY; CLASSIFICATION PERFORMANCE; COMPONENT ANALYSIS; EEG SIGNAL CLASSIFICATION; EEG SIGNALS; FEATURE SELECTION ALGORITHM; FEATURE VECTORS; K-NN CLASSIFIER; MOTHER WAVELETS; NUMBER OF ZEROS; STANDARD DEVIATION; SUB-BANDS;

ALGORITHMS; BRAIN; COMMUNICATION; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING; WAVELET TRANSFORMS;

FEATURE EXTRACTION;

EID: 80053166334     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCSN.2011.6014686     Document Type: Conference Paper

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