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中文摘要：
当前复杂网络的研究已经成为脑电信号研究的热点。因为脑电网络产生的时间序列保存了网络结点信息，因此研究网络产生的时间序列同样能够达到研究癫痫脑电信号的目的。基于此，本文提出了一种基于改进的k-最近邻网络产生时间序列来分析癫痫脑电信号的方法。研究结果表明，研究网络产生的时间序列的功率谱比直接研究原始癫痫脑电信号的功率谱更容易区分正常人和癫痫患者。此外，研究改进的k-最近邻网络的聚类系数也能区分正常人和癫痫患者。通过本文研究结果，期望能够为癫痫研究及其今后的临床诊断提供相关参考依据。
英文摘要：
The study of complex networks has become a hot research area of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so studying the time series from the network can also achieve the purpose of study epileptic electroencephalogram. In this paper, we propose a method to analyze epileptic electroencephalogram based on time series which is based on improved k-nearest neighbor network. The results of the experiment showed that studying power spectrum of time series from network was easier than power spectrum of time series directly generated from the original brain data to distinguish between normal controls and epileptic patients. In addition, studying the clustering coefficient of improved k-nearest neighbor network was able to distinguish between normal persons and patients with epilepsy. This study can provide important reference for the study of epilepsy and clinical diagnosis.
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