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基于分数低阶矩的非高斯噪声中诱发电位提取新方法 被引量：3

Blind Estimation of Evoked Potentials Based on Fractional Lower Order Moments
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摘要 诱发电位(EP)信号检测与分析技术是临床医学诊断神经系统损伤及病变的重要手段之一。传统的EP信号提取与分离方法中,通常认为EP信号中混入的EEG等噪声是高斯分布的。近年来一些研究表明了EEG信号具有一定的非高斯特性。α-稳定分布可以更好地描述实际应用中所遇到的具有显著脉冲特性的EEG噪声。文中简要介绍了稳定分布统计特性,推导了一种适用于EP信号分离提取的新算法。计算机模拟和分析表明,这种算法是一种在分数低阶α稳定分布背景噪声条件下具有良好韧性的EP信号分离提取方法。 Evoked potentials （EPs） have been widely used to quantify neurological system properties. Traditional EP analysis has been developed under the condition that the background noises in EP are Gaussian distributed. Recently it is accepted that Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noises than Gaussian distribution in biomedical signal processing. Conventional blind separation and estimation method of evoked potentials is based on the second order statistics. In this paper, we modify conventional algorithms and analyze the stability and convergence performances of the new algorithm. The simulation experimental results show that the proposed new algorithm is more robust than the conventional algorithm.
作者 查代奉 邱天爽
机构地区 大连理工大学电子与信息工程学院
出处 《中国生物医学工程学报》 CAS CSCD 北大核心 2006年第1期41-45,57,共6页 Chinese Journal of Biomedical Engineering
基金 国家自然科学基金资助项目(60372081 60172072 30170259 30570475) 教育部博士点基金(20050141025)
关键词 诱发电位 α-稳定分布 二阶统计量 分数低阶统计量 evoked potentials alpha stable distribution second order statistics fractional lower order statistics
分类号 R318 [医药卫生—生物医学工程]
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参考文献14

  • 1Gharieb RR, Cichacki A. Noise reduction in brain evoked potentials based on third-order correlations[J]. IEEE Transactions on Biomedical Engineering. 2001, 48(5) : 501 - 512.
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共引文献51

同被引文献27

  • 1查代奉,邱天爽.基于分数阶谱的频域广义白化滤波方法[J].通信学报,2005,26(5):24-30. 被引量：15
  • 2邱天爽,查代奉.基于分数低阶统计量的水下目标定向新方法[J].系统工程与电子技术,2006,28(7):941-945. 被引量：1
  • 3Gharieb RR, Cichocki A. Noise reduction in brain evoked potentials based on third-order correlations [ J ]. IEEE Transactions on Biomedical Engineering, 2001, 48(5) : 501 - 512.
  • 4Davila CE, Srebro R, Ghaleb IA. Optimal detection of visual evoked potential [J]. IEEE Transaction on Biomedical Engineering, 1998, 45(6) : 800 - 803.
  • 5Hazarika N, Tsoi AC, Sergejew AA. Nonlinear considerations in EEG signal classification [ J ]. IEEE Trans. Signal Processing, 1997, 45 : 829 - 936.
  • 6Ma X, Nikias CL. Joint estimation of time delay and frequency delay in impulsive noise using fractional lower -order statistics [ J].IEEE Trans. on Signal Processing, 1996, 44: 2669- 2687.
  • 7Shao M, Nikias CL. Signal Processing with fractional lower order moments : stable processes and their applications [ C ]. Proceedings of IEEE, 1993, 81(7) : 986 - 1010.
  • 8Kong X, Qiu T. Adaptive estimation of latency change in evoked potentials by direct least mean p-norm time-delay estimation [ J]. IEEE Transactions on Biomedical Engineering, 1999, 46(8) : 994 - 1003.
  • 9Gennady S, Taqqu MS. Stable Non-Gaussian Random Processes. Chapman&Hall, 1994. 189-193.
  • 10Tewon L, Mark G, Terrenc E, et al. Independent component analysis using all extended infomax algorithm for mixed subgaussian and supergausslan source [J]. Neural Computation, 1999,11(1):417-441.

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中国生物医学工程学报
2006年 第1期

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