换一批摘要Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface.Firstly,discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time.The reconstructed signal of approximation coefficient A6 on the 6th level was selected to build up a feature signal.Secondly,the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared.The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.
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分类号
R318.04（医用一般科学）
栏目名称
发布时间
2012-05-25（万方平台首次上网日期，不代表论文的发表时间）
基金项目
:The Open Project of the State Key Laboratory of Robotics and System
:the State Key Laboratory of Cognitive Neuroscience and Learning
Natural Science Fund for Colleges and Universities in Jiangsu Province（grant sponsor）
105TB51003（grant number）
Natural Science Fund in Changzhou（grant sponsor）
C J20110023（grant number）
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