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中文摘要：
为了提高皮层脑电图（ECoG）脑-机接口（BCI）的分类精度,提出了基于运动想象的ECoG频域模式滤波法.该方法通过联合对角化寻找最具判别力的投影方向作为频域滤波器,抽取滤波后ECoG的均值和标准差作为特征,然后采用核Fisher判别式进行分类.BCI2005数据集Ⅰ的实验结果表明：采用该方法仅用单个电极即可获得92%的测试精度.
英文摘要：
In order to improve the classification accuracy of the brain-computer interface（BCI） of electrocortico-graphy（ECoG）,a motor imagery-based pattern-filtering method in frequency domain is proposed.In this method,the joint diagonalization is employed to seek the most discriminative projections as the frequency-domain filters,the means and standard deviations of filtered electrocorticograms are extracted as the features,and the kernel Fisher discriminant is applied to the classification.Experimental results of BCI2005 data set Ⅰ show that the proposed method can achieve a classification accuracy of 92% even with a single electrode.
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