Approximate entropy and support vector machines for electroencephalogram signal classification

doi:10.3969/j.issn.1673-5374.2013.20.003

Neural Regeneration Research ›› 2013, Vol. 8 ›› Issue (20): 1844-1852.doi: 10.3969/j.issn.1673-5374.2013.20.003

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Approximate entropy and support vector machines for electroencephalogram signal classification

Zhen Zhang¹, Yi Zhou¹, Ziyi Chen², Xianghua Tian³, Shouhong Du³, Ruimei Huang¹

1 Department of Biomedical Engineering, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, China
2 Department of Neurology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, Guangdong Province, China
3 College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830011, Xinjiang Uygur Autonomous Region, China

Received:2013-03-17 Revised:2013-06-18 Online:2013-07-15 Published:2013-07-15
Contact: Yi Zhou, M.D., Master’s supervisor, Associate professor, Department of Biomedical Engineering, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, Guangdong Province, China, zhouyi@mail.sysu.edu.cn.
About author:Zhen Zhang, Master.

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Zhen Zhang, Yi Zhou, Ziyi Chen, Xianghua Tian, Shouhong Du, Ruimei Huang. Approximate entropy and support vector machines for electroencephalogram signal classification[J]. Neural Regeneration Research, 2013, 8(20): 1844-1852.

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Approximate entropy and support vector machines for electroencephalogram signal classification

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