Pattern Recognition and Image Analysis

, Volume 25, Issue 2, pp 321–326 | Cite as

Classification of steady state visual evoked potentials by Multi-Class T-Weight Method

  • Z. IscanEmail author
  • Z. Dokur
Applied Problems


In this paper, Multi-Class T-Weight Method (MCTW) is presented for classification in brain-computer interface (BCI) systems. Proposed method is an extension of the existing Improved T-Weight method for multi-class problems. The method was tested on the frequency and correlation based features obtained from electroencephalogram data of 20 Subjects in a steady state visual evoked potential (SSVEP) based offline BCI classification task. Obtained classification performances with different classifiers show that the MCTW method compete with the other well-known classifiers like linear discriminant analysis (LDA) and support vector machines (SVMs). Therefore, it can be used in classifying SSVEP based electroencephalogram data with proper features.


obtained classification performances applications of MCTW method 


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Copyright information

© Pleiades Publishing, Ltd. 2015

Authors and Affiliations

  1. 1.Department of Psychiatry and Behavioral SciencesStony Brook UniversityStony BrookUSA

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