论文标题
数据集之间的非线性特征分解光谱和阶段差异
Decomposing spectral and phasic differences in non-linear features between datasets
论文作者
论文摘要
当采用非线性方法表征复杂系统时，重要的是要确定它们在多大程度上捕获了真正无法通过简单的光谱方法评估的真正的非线性现象。具体而言，我们关注的是对两个系统（或同一系统的两个状态）之间观察到的频谱和相位影响的问题。在这里，我们从一系列无效模型中得出，可观察到的差异分解为光谱，阶段和光谱相互作用成分。我们的方法对数据的结构没有任何假设，并增加了广泛的时间序列分析。
When employing non-linear methods to characterise complex systems, it is important to determine to what extent they are capturing genuine non-linear phenomena that could not be assessed by simpler spectral methods. Specifically, we are concerned with the problem of quantifying spectral and phasic effects on an observed difference in a non-linear feature between two systems (or two states of the same system). Here we derive, from a sequence of null models, a decomposition of the difference in an observable into spectral, phasic, and spectrum-phase interaction components. Our approach makes no assumptions about the structure of the data and adds nuance to a wide range of time series analyses.
