Circular Correlation Methods for the Analysis of Oscillations in Dependent Time Series
Circular Correlation Methods for the Analysis of Oscillations in Dependent Time Series
复制标题
用于分析相关时间序列振荡的循环相关方法
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
G. Ivanova
中科院分区：
文献类型：
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作者：
U. Jentsch;G. Ivanova
信号的相位可以看作是循环数据。阶段的时间序列在统计上依赖于时间。不同的循环时间序列之间也存在相关性。我们使用循环相关系数来量化现有的相关性，而不是像相位相干性这样的相对相位法。基于这个系数，我们建立了相关矩阵。在仿真验证后，将该方法应用于脑电信号的相位时间序列。该方法得到了验证，可用于振荡检测和考虑相位信息的时间序列之间的耦合。
Phases of signals can be regarded as circular data. Time series of phases statistically depend in time. There are also dependencies between diverse circular time series. Instead of relative-phase-methods such as phase-coherence we use a circular correlation coefficient to quantify existing dependence. Based on this coefficient we built correlation matrices. After validation in simulations, we applied the method to phase time series of electroencephalographic data. The method, developed, was positively tested and can be used for oscillation detection and to find couplings between time series considering phase information.