A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography

DOI10.1063/1.4812287zbMath1331.37122OpenAlexW1974558862WikidataQ51191262 ScholiaQ51191262MaRDI QIDQ2787848

Socrates Dokos, Hong-Bo Xie

Publication date: 4 March 2016

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1063/1.4812287

Mathematics Subject Classification ID

Time series analysis of dynamical systems (37M10) Simulation of dynamical systems (37M05) Random dynamical systems (37H99)

Cites Work

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• Constrained-realization Monte-Carlo method for hypothesis testing
• Detecting high-dimensional determinism in time series with application to human movement data
• On noise reduction methods for chaotic data

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