Abstract: Eye movement and eye blink artifacts constantly influence the acquisition and analysis of EEG signals.In this paper，a robust algorithm based on the combination of Principal Component Analysis（PCA） and Joint Approximative Diagonalization of Eigen matrix（JADE） is presented.Besides，the influence of PCA on the performance is discussed.The experimental results demonstrate that the proposed method is efficient and robust，and especially having the essential capability of reducing processing time.Furthermore，it can reject other kinds of noises and artifacts.

摘要： 眼电伪迹干扰是脑电信号中的常见干扰，严重影响到有用脑电信号的提取和分析。提出一种基于主分量分析（PCA）和特征矩阵联合相似对角化（JADE）算法相结合的眼电伪迹去除方法，并探讨了主分量分析对伪迹去除的影响。实验结果表明了该算法的有效性及稳健性，并且其时间开销小。此外该算法还可以有效去除其他脑电伪迹及干扰成分。