A polynomial fitting and k-NN based approach for improving classification of motor imagery BCI data

Pattern Recognition Letters

Volumn 31, Issue 11, 2010, Pages 1207-1215

  Kayikcioglu, Temel ^a   Aydemir, Onder ^a  

^a KARADENIZ TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Brain computer interface (BCI); Classification; Electroencephalogram (EEG); Feature extraction; k Nearest neighbor; Polynomial fitting

Indexed keywords

BRAIN COMPUTER INTERFACE (BCI); CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; CURSOR MOVEMENT; DATA SETS; ELECTROENCEPHALOGRAPHIC SIGNALS; K-NEAREST NEIGHBORS; K-NN ALGORITHM; KEY ISSUES; MOTOR IMAGERY; MULTIPLE LAYER PERCEPTRON; NN-BASED APPROACH; POLYNOMIAL FITTINGS; SECOND-ORDER POLYNOMIAL; SUPPORT VECTOR MACHINE ALGORITHM; TRAINING AND TESTING; TWO-DIMENSIONAL FEATURES;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; FUZZY CONTROL; IMAGE RETRIEVAL; INTERFACES (COMPUTER); POLYNOMIALS;

BRAIN COMPUTER INTERFACE;

EID: 77953131563     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2010.04.009     Document Type: Article

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