%0 Journal Article
%T Electroencephalograph analysis based on complex networks<br>基于复杂网络的脑电信号分析
%A HAO Chong-qing
%A WANG Jiang
%A DENG Bin
%A WEI Xi-le
%A <br>郝崇清
%A 王　江
%A 邓　斌
%A 魏熙乐
%J 计算机应用研究
%D 2012
%I 
%X This paper investigated one dimension EEG by converting it into complex networks via phase space reconstruction. To construct a complex networks, regarded each vector point as a node, and determined the edges by the phase space distance of each pair of vector points. A selective threshold value, which made the complex networks satisfy connectivity, could transform the distance matrix into a binary matrix. The binary matrix viewed as the adjacent matrix of complex networks was used to draw network topology and to analyze network characteristics. Applied the constructing networks method to distinguish EEG during eye-open and eye-closed resting conditions. The results indicate that recurrence plot, network topology, degree distribution and motifs distribution of the two networks show a distinct difference. Therefore complex networks as a data representation framework provide a new way for analyzing and distinguishing electroencephalograph.
%K complex networks
%K electroencephalograph
%K phase space reconstruction
%K recurrence plot
%K motifs distribution<br>复杂网络
%K 脑电图
%K 相空间重构
%K 递归图
%K 模体分布
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=38AAB79AD8A56B532FF081AAFC9A0982&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=F3090AE9B60B7ED1&sid=448FB17DFCBFA1B0&eid=E21FA0DB4B93566E&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=25