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基于独立分量分析的脑电信号的眼电伪迹消除 被引量：3

Removing EOG artifacts from EEG signal based on ICA
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摘要 介绍了独立分量分析技术的基本概念和原理,及其具有代表性的基于负熵最大的快算独立分量分析算法和基于核空间的独立分量分析算法,并分别对脑电中的眼电伪迹进行去除。通过仿真实验表明了独立分量分析算法较快速独立分量分析算法能更好去除眼电伪迹,具有较好准确性和鲁棒性。 This paper introduces a new technology Independent Component Analysis （ICA）,including its basic concepts,principles,and some representative algorithms,such as Fast Independent Component Analysis （FICA） and Kernel Independent Component Analysis（KICA）.The method of removing EOG artifact from EEG Data was proposed.Simulation results show that KICA algorithm can remove EOG artifact from the EEG signal better,and it is also more accurate and robust than FICA.
作者 李营 艾玲梅
机构地区 陕西师范大学计算机科学学院
出处 《计算机工程与应用》 CSCD 北大核心 2009年第15期209-212,共4页 Computer Engineering and Applications
基金 陕西师范大学校级资助项目(No.200802019)
关键词 独立分量分析 脑电信号 快速独立分量分析 核独立分量分析 Independent Component Analysis （ICA） electroencephalogram （EEG） Fast Independent Component Analysis（FICA） Kernel Independent Component Analysis（KICA）
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献7

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二级参考文献17

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共引文献12

同被引文献26

  • 1唐艳,汤井田.基于独立分量分析的脑电中眼电伪迹消除[J].中国医学物理学杂志,2006,23(5):380-383. 被引量：2
  • 2XU Jin, LI Wenwen, ZHENG Congxun, et al. Noninvasive detection of brain activity variation under different depth of an- esthesia by EEG complexity[J. Academie Journal of Xi' an Jiaotong University (English Edition), 2006, 18(1) 36-39.
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  • 10施宁,王行愚,邹俊忠,王蓓.一种改进的加权中值滤波器及其在眼电信号处理中的应用[J].生物医学工程学杂志,2007,24(5):1069-1072. 被引量：2

引证文献3

二级引证文献9

计算机工程与应用
2009年 第15期

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