使用细胞非线性网络估计动态系统中的相位同步。
Estimating phase synchronization in dynamical systems using cellular nonlinear networks.
作者信息
Sowa Robert, Chernihovskyi Anton, Mormann Florian, Lehnertz Klaus
机构信息
Department of Epileptology, Neurophysics Group, University of Bonn, Sigmund-Freud-Strasse 25, D-53105 Bonn, Germany.
出版信息
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 1):061926. doi: 10.1103/PhysRevE.71.061926. Epub 2005 Jun 29.
We propose a method for estimating phase synchronization between time series using the parallel computing architecture of cellular nonlinear networks (CNN's). Applying this method to time series of coupled nonlinear model systems and to electroencephalographic time series from epilepsy patients, we show that an accurate approximation of the mean phase coherence R--a bivariate measure for phase synchronization--can be achieved with CNN's using polynomial-type templates.
我们提出了一种利用细胞非线性网络（CNN）的并行计算架构来估计时间序列之间相位同步的方法。将该方法应用于耦合非线性模型系统的时间序列以及癫痫患者的脑电图时间序列，我们表明，使用多项式类型模板的CNN可以实现对平均相位相干性R（一种用于相位同步的双变量度量）的精确近似。
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