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基于互信息与主成分分析的运动想象脑电特征选择算法
Authors
左国坤
徐佳琳
Publication date
1 January 2016
Publisher
Abstract
针对脑机接口中运动想象任务的特征选择问题,提出一种基于互信息与主成分分析的脑电特征选择算法。该算法融入类别信息,用不同运动想象类别条件下特征间的互信息矩阵之和取代传统主成分分析算法中的协方差矩阵,其特征向量表示新的主成分空间内各主成分的方向,特征值则作为评价准则判断主成分维数。对2005年国际BCI竞赛数据集,联合功率谱估计、连续小波变换、小波包分解、Hjorth参数四种方法进行特征提取,采用所提出的算法进行特征选择并与主成分分析算法对比,实验结果表明,所提出算法的降维效果更好,以支持向量机为分类器,相同维数的主成分,所得分类正确率更高
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Last time updated on 22/01/2018