Design of support vector machines with time frequency kernels for classification of EEG signals

TechSym 2010 - Proceedings of the 2010 IEEE Students' Technology Symposium

Volumn , Issue , 2010, Pages 330-333

  Kumar, Anurag ^b   Mohanty, Mihir N ^a   Routray, Aurobinda ^b  

^a SIKSHA O ANUSANDHAN DEEMED TO BE UNIVERSITY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

EEG classification; Support vector machine; Time frequency kernels

Indexed keywords

CLASSIFICATION METHODS; CLASSIFICATION PERFORMANCE; COHEN'S CLASS; COMMON FEATURES; COMPARATIVE ASSESSMENT; EEG CLASSIFICATION; EEG SIGNALS; FEATURE SPACE; FEATURE VECTORS; FREQUENCY DOMAINS; GAUSSIAN KERNELS; INPUT DATAS; MENTAL TASKS; NONSTATIONARY; SVM CLASSIFIERS; TIME FREQUENCY; TIME FREQUENCY KERNELS; TIME-FREQUENCY TRANSFORMATION; WIGNER VILLE;

FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; MACHINE DESIGN; METADATA; SUPPORT VECTOR MACHINES; VECTORS; WAVELET TRANSFORMS;

ELECTROENCEPHALOGRAPHY;

EID: 77953886415     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/TECHSYM.2010.5469169     Document Type: Conference Paper

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