Intrinsic recurrence quantification analysis of nonlinear and nonstationary short-term time series
Author:
Affiliation:
1. Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Binghamton, New York 13902, USA
2. Smart Health Laboratory, Hebei University of Technology, Tianjin 300000, China
Funder
Natural Science Foundation of Hebei Province
Lois B. DeFleur International Innovation Fund
Publisher
AIP Publishing
Subject
Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0006537
Reference30 articles.
1. Time series forecasting for nonlinear and non-stationary processes: a review and comparative study
2. Forecasting the evolution of nonlinear and nonstationary systems using recurrence-based local Gaussian process models
3. Multi-scale Gaussian process experts for dynamic evolution prediction of complex systems
4. Inferring power-grid topology in the face of uncertainties
5. Nonlinear adaptive wavelet analysis of electrocardiogram signals
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