Classification of electroencephalography (EEG) signals for different mental activities using Kullback Leibler (KL) divergence

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 1697-1700

  Gupta, Anjum ^a   Parameswaran, Shibin ^b   Lee, Cheng Han ^c  

^a SSC   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Brain computer interface; Electroencephalography; Kullback Liebler (KL) divergence; Pattern classification; Support vector machines

Indexed keywords

ACTIVE AREA; ARTIFACT REMOVAL; AUTOMATIC CLASSIFICATION; BRAIN COMPUTER INTERFACE; CLASSIFICATION ,; CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; DATA SETS; DISTANCE MEASURE; DISTANCE-BASED; EEG SIGNALS; EUCLIDEAN; FEATURE VECTORS; K-NEAREST NEIGHBORS; KL-DIVERGENCE; KULLBACK-LEIBLER DIVERGENCE; KULLBACK-LIEBLER (KL) DIVERGENCE; MATH PROBLEM SOLVING; MEDICAL DIAGNOSIS; MENTAL ACTIVITY; PATTERN CLASSIFICATION; PRE-PROCESSING STEP; RADIAL BASIS FUNCTIONS;

ACOUSTICS; AUTOMATIC INDEXING; BRAIN; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; IMAGE RETRIEVAL; RADIAL BASIS FUNCTION NETWORKS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; VECTORS;

INTERFACES (COMPUTER);

EID: 70349208603     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4959929     Document Type: Conference Paper

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