计算物理 ›› 2007, Vol. 24 ›› Issue (5): 612-618.

• 研究论文 • 上一篇    下一篇

Liley模型的模拟EEG信号的非线性预测和分析

王兴元, 谭贵霖   

  1. 大连理工大学电子与信息工程学院, 辽宁 大连 116024
  • 收稿日期:2006-05-19 修回日期:2006-08-21 出版日期:2007-09-25 发布日期:2007-09-25
  • 作者简介:王共元(1964-),男,辽宁沈阳,教授,博导,博士,从事混沌分形理论及应用方面的研究.
  • 基金资助:
    国家自然科学基金(批准号:60573172);辽宁省教育厅高等学校科学技术研究计划(批准号:20040081)资助项目

Nonlinear Prediction and Analysis of EEG in a Liley Model

WANG Xingyuan, TAN Guilin   

  1. School of Electronic & Information Engineering, Dalian University of Technology, Dalian 116024, China
  • Received:2006-05-19 Revised:2006-08-21 Online:2007-09-25 Published:2007-09-25

摘要: 分析Liley模型的模拟脑电(Electroencephalogram,EEG)信号的非线性预测和径向基函数(Radial Basis Functions,RBF)神经网络预测,利用相图分析和非线性正交预测(Nonlinear Cross-Prediction,NLCP)方法研究模拟EEG信号.结果发现:①RBF神经网络预测的效果要好于非线性预测;②NLCP方法对含有强周期分量的高维系统具有较好的适用性;③支持了EEG中存在混沌运动的观点.

关键词: Liley模型, 脑电, 非线性正交预测, 径向基函数神经网络预测, 混沌

Abstract: Nonlinear prediction and RBF (Radial Basis Functions) neural network prediction of EEG(Electroencephalogram) signal in a Liley model are studied by phase graph and NLCP (Nonlinear Cross-Prediction).It concluded that:1) RBF neural network prediction is better than nonlinear prediction;2) NLCP method is adaptive to time series with strong periodic components;3) support the exist of chaos in EEG signals.

Key words: Liley model, Electroencephalogram, Nonlinear Cross-Predication, Radial Basis Functions neural network prediction, chaos

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