Reciprocal characterization from multivariate time series to multilayer complex networks
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Publication:5218169
DOI10.1063/1.5112799zbMath1437.62344OpenAlexW3001428182WikidataQ89512397 ScholiaQ89512397MaRDI QIDQ5218169
Michael Small, Yi Zhao, Xiaoyi Peng
Publication date: 28 February 2020
Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1063/1.5112799
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Cites Work
- Complex network approach for recurrence analysis of time series
- Visibility graphs and symbolic dynamics
- Characterizing pseudoperiodic time series through the complex network approach
- Windows of opportunity for synchronization in stochastically coupled maps
- Patterns and coherence resonance in the stochastic Swift-Hohenberg equation with Pyragas control: the Turing bifurcation case
- Scaling features of intermittent dynamics: differences of characterizing correlated and anti-correlated data sets
- Using permutations to detect dependence between time series
- Detecting changes in coupling with Granger causality method from time series with fast transient processes
- RECURRENCE-BASED TIME SERIES ANALYSIS BY MEANS OF COMPLEX NETWORK METHODS
- Recurrence networks—a novel paradigm for nonlinear time series analysis
- From time series to complex networks: The visibility graph
- The $25,000,000,000 Eigenvector: The Linear Algebra behind Google
- Recurrences determine the dynamics
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Distributed Adaptive Control of Synchronization in Complex Networks
- On Applicability of Auxiliary System Approach to Detect Generalized Synchronization in Complex Network
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