Cross-correlations between signal's components  

作　　者：Quankun Zhao Sen Li Changgui Gu Haiying Wang Huijie Yang 赵全坤;李森;顾长贵;王海英;杨会杰

机构地区：[1]Department of Systems Science,University of Shanghai for Science and Technology,Shanghai 200093,China

出　　处：《Chinese Physics B》2025年第2期483-494,共12页中国物理B(英文版)

基　　金：Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114);the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。

摘　　要：Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.

关 键 词：coupling structure cross-correlation matrix component correlation network 

分 类 号：O157.5[理学—数学]