光谱相关性

摘要：

本文提出了一个通用的框架，在多变量时间序列的依赖建模。它的基本方法是将系统中的每个信号分解为不同的频率分量，然后通过这些振荡活动研究相关性。本文的统一主题是通过滤波来探索相关性的强度和可能的超前滞后动态。所提出的框架是能够代表线性和非线性的依赖关系，可能会发生瞬间或经过一定的延迟（滞后依赖）。研究振荡之间的依赖性的例子说明通过多通道脑电图。这些例子强调，一些最突出的频域措施，如相干性，部分相干性，双频相干性可以推导出作为特殊情况下，在这个一般框架。本文还介绍了相关的方法，通过相位-幅度耦合和因果关系的（单侧）滤波信号的建模依赖。

英文摘要：

This paper presents a general framework for modeling dependence in multivariate time series. Its fundamental approach relies on decomposing each signal in a system into various frequency components and then studying the dependence properties through these oscillatory activities.The unifying theme across the paper is to explore the strength of dependence and possible lead-lag dynamics through filtering. The proposed framework is capable of representing both linear and non-linear dependencies that could occur instantaneously or after some delay(lagged dependence). Examples for studying dependence between oscillations are illustrated through multichannel electroencephalograms. These examples emphasized that some of the most prominent frequency domain measures such as coherence, partial coherence,and dual-frequency coherence can be derived as special cases under this general framework.This paper also introduces related approaches for modeling dependence through phase-amplitude coupling and causality of (one-sided) filtered signals.

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