Classification of EEG Signals by using Support Vector Machines

被引：0

作者：

Bayram, K. Sercan ^{[1
]}

Kizrak, M. Ayyuce ^{[1
]}

Bolat, Bulent ^{[2
]}

机构：

[1] Halic Univ, Elect & Elect Eng Dpt, Istanbul, Turkey

[2] Yildiz Tech Univ, Elect Commun Eng Dpt, Istanbul, Turkey

来源：

2013 IEEE INTERNATIONAL SYMPOSIUM ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (IEEE INISTA) | 2013年

关键词：

EEG; suport vector machines; feature selection;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, EEG signals were classified by support vector machines to detect whether a subject's planning to perform a task or not. Various different kernels were utilized to find the best kernel function and after that, a feature selection process was realized. The results are comparable to the recent works.

引用

页数：3

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