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基于复杂网络的脑电信号回归分析
引用本文:蔡世民,洪磊,傅忠谦,周佩玲.基于复杂网络的脑电信号回归分析[J].中国科学技术大学学报,2011,41(4).
作者姓名:蔡世民  洪磊  傅忠谦  周佩玲
作者单位:中国科学技术大学电子科学与技术系,安徽合肥,230027
基金项目:国家自然科学基金,教育部博士后基金,王宽诚博士后基金,中央高校基本科研业务费专项基金
摘    要:基于相点距离集合确定脑电信号的相空间重构嵌入维数,并得到时间序列的相空间轨迹.把由相空间轨迹构成的回归矩阵转化为复杂网络的连接矩阵,并用复杂网络的特征参量表征回归矩阵的性质.实验结果表明,由不同生理状态的脑电信号构成的回归矩阵呈现出普适和非普适特征,也就是小世界特征的一致性和聚类结构的差异性.这些结论与实际脑网络的小世界特征和脑功能区域的聚类结构能够很好吻合.

关 键 词:复杂网络  脑电信号  回归分析  小世界

Complex-network-based approach to recurrence analysis of EEG
CAI Shimin,HONG Lei,FU Zhongqian,ZHOU Peiling.Complex-network-based approach to recurrence analysis of EEG[J].Journal of University of Science and Technology of China,2011,41(4).
Authors:CAI Shimin  HONG Lei  FU Zhongqian  ZHOU Peiling
Institution:CAI Shimin,HONG Lei,FU Zhongqian,ZHOU Peiling(Department of Electronical Science and Technology,University of Science and Technology of China,Hefei 230027,China)
Abstract:The phase-space trajectories of EEG signals were obtained via determining embedding dimension in phase-space reconstruction based on the distance set of space points.The recurrence matrix calculated from phase-space trajectories was identified with the adjacency matrix of a complex network and measured by the characterisation of complex networks.The results show that the small-world characteristic of recurrence matrix exists in all physiological states,while the cluster structure of that changes with differ...
Keywords:complex networks  EEG  recurrence analysis  small-world  
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