Classification of EEG signals using sampling techniques and least square support vector machines

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5589 LNAI, Issue , 2009, Pages 375-382

  Siuly, ^a   Li, Yan ^a   Wen, Peng ^b  

^a Department of Mathematics and Computing ^*  (Australia)

^b UNIVERSITY OF SOUTHERN QUEENSLAND   (Australia)

Author keywords

Ampling techniques (ST); Electroencephalogram (EEG); Least square support vector machines (LS SVM); Simple random sampling (SRS)

Indexed keywords

AMPLING TECHNIQUES (ST); CLASSIFICATION ACCURACY; EEG SIGNALS; ELECTROENCEPHALOGRAM (EEG); ELECTROENCEPHALOGRAM SIGNALS; EPILEPTIC PATIENTS; EPILEPTIC SEIZURES; FEATURE VECTORS; LEAST SQUARE SUPPORT VECTOR MACHINES; LEAST SQUARE SUPPORT VECTOR MACHINES (LS-SVM); SAMPLING TECHNIQUE; SIMPLE RANDOM SAMPLING (SRS); TIME-SERIES DATA; TRAINING AND TESTING; TWO STAGE;

ELECTROENCEPHALOGRAPHY; EXTRACTION; FEATURE EXTRACTION; FUZZY SETS; GEARS; IMAGE RETRIEVAL; INTERACTIVE COMPUTER SYSTEMS; MULTILAYER NEURAL NETWORKS; OPTICAL SENSORS; ROUGH SET THEORY; SETTLING TANKS; STIMULATED RAMAN SCATTERING; TIME SERIES; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 69049087866     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02962-2_47     Document Type: Conference Paper

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