| 独立分量分析的拟牛顿迭代算法及其在视觉诱发电位特征提取中的应用 |
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| 引用本文： | 李晓欧,江朝晖,张笑微,冯焕清.独立分量分析的拟牛顿迭代算法及其在视觉诱发电位特征提取中的应用[J].生物医学工程学杂志,2006,23(1):45-48. |
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| 作者姓名： | 李晓欧 江朝晖 张笑微 冯焕清 |
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| 作者单位： | 1. 中国科学技术大学,电子科学与技术系,合肥,230026
2. 西南科技大学,信控学院,绵阳,621002 |
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| 摘 要： | 少次叠加平均处理后的视觉诱发电位（VEP）中仍含有一定的背景噪声．对其进行进一步的提取与处理有重要的实用价值。独立分量分析（ICA）能够从混合信号中分离出最独立的成分，有效抑制噪声。本文尝试采用ICA的拟牛顿迭代算法进行VEP特征提取，介绍该方法的原理、实验和结果，并与采用牛顿迭代准则的快速独立孕量分析（Fast ICA）算法进行了比较。结果表明，基于拟牛顿法的ICA可以有效增强信号，从少次叠加平均的结果中提取出易于辨识的VEP的P300信号，具有较高的应用价值。
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| 关 键 词： | 独立分量分析 拟牛顿法 视觉诱发电位 |
| 收稿时间： | 2003-09-10 |
| 修稿时间： | 2003-09-102004-02-11 |
Quasi-Newton Iteration Algorithm for ICA and Its Application in VEP Feature Extraction |
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| Li Xiao'ou,Jiang Zhaohui,Zhang Xiaowei,Feng Huanqing.Quasi-Newton Iteration Algorithm for ICA and Its Application in VEP Feature Extraction[J].Journal of Biomedical Engineering,2006,23(1):45-48. |
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| Authors: | Li Xiao'ou Jiang Zhaohui Zhang Xiaowei Feng Huanqing |
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| Institution: | Department of Electronic Science & Technology, USTC, Hefei 230026, China. |
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| Abstract: | Some noises still exist in the single-trial averaged visual evoked potentials(VEP),so further extraction of the above results is of significance.Independent component analysis(ICA)can separate the sources from their mixtures and make the output statistically as independent as possible;it can remove noises effectively.In this paper,the principle,experiment analyses and results of ICA based on quasi-Newton iteration rule for VEP feature extraction are introduced,It is compared with the fixed-point FastICA algorithm.The experiment results show that the provided algorithm may reinforce signals effectively and extract distinct P300 from the single-trial averaged VEP.It is of good applicability. |
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| Keywords: | P300 |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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