Harmonic cross-correlation decomposition for multivariate time series
نویسندگان
چکیده
We introduce harmonic cross-correlation decomposition (HCD) as a tool to detect and visualize features in the frequency structure of multivariate time series. HCD decomposes series into spatiotemporal modes with leading representing dominant oscillatory patterns data. is closely related data-adaptive (DAHD) [Chekroun Kondrashov, Chaos 27, 093110 (2017)] that it performs an eigendecomposition grand matrix containing lagged cross-correlations. As for DAHD, each mode uniquely associated Fourier frequency, which allows definition multidimensional power phase spectra. Unlike however, does not exhibit systematic dependency on ordering channels within matrix. Further, spectra can be relations data intuitive way. compare DAHD singular spectrum analysis, third correlation-based decomposition, we give illustrative applications simple traveling wave, well simulations three coupled Stuart-Landau oscillators human EEG recordings.
منابع مشابه
Correlation based dynamic time warping of multivariate time series
0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.05.012 ⇑ Corresponding author. Tel.: +36 88 624209. E-mail address: [email protected] (J. Ab In recent years, dynamic time warping (DTW) has begun to become the most widely used technique for comparison of time series data where extensive a priori knowledge is not available. However, it is often expe...
متن کاملA nonparametric regression cross spectrum for multivariate time series
We consider dependence structures in multivariate time series that are characterized by deterministic trends. Results from spectral analysis for stationary processes are extended to deterministic trend functions. A regression cross covariance and spectrum are defined. Estimation of these quantities is based on wavelet thresholding. The method is illustrated by a simulated example and a three-di...
متن کاملCross-Correlation Dynamics in Financial Time Series
The dynamics of the equal-time cross-correlation matrix of multivariate financial time series is explored by examination of the eigenvalue spectrum over sliding time windows. Empirical results for the S&P 500 and the Dow Jones Euro Stoxx 50 indices reveal that the dynamics of the small eigenvalues of the cross-correlation matrix, over these time windows, oppose those of the largest eigenvalue. ...
متن کاملAttribute-Based Time Series Cross-Correlation Measures
Datasets are usually compared using cross-correlation, often using a moving window to calculate the correlation as a function of time or space. However, signals can be considered as being composed of sinusoids which possess amplitudes, frequencies and phases. All these three attributes can be computed at each point in time, and then used as the basis of a cross-correlation method. By using all ...
متن کاملDecomposition of neurological multivariate time series by state space modelling.
Decomposition of multivariate time series data into independent source components forms an important part of preprocessing and analysis of time-resolved data in neuroscience. We briefly review the available tools for this purpose, such as Factor Analysis (FA) and Independent Component Analysis (ICA), then we show how linear state space modelling, a methodology from statistical time series analy...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review E
سال: 2021
ISSN: ['1550-2376', '1539-3755']
DOI: https://doi.org/10.1103/physreve.103.062213