MODELING NONLINEAR DETERMINISM IN SHORT TIME SERIES FROM NOISE DRIVEN DISCRETE AND CONTINUOUS SYSTEMS

DOI10.1142/S021812740000178XzbMath0972.37057OpenAlexW1981906309MaRDI QIDQ2709998

Ki H. Chon, B. M. Camino, Niels-Henrik Holstein-Rathlou, Donald J. Marsh, Kay-Pong Yip

Publication date: 13 July 2001

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s021812740000178x

zbMATH Keywords

short time seriesfast orthogonal search algorithmnoise driven systemstochastic nonlinear autoregressive model

Mathematics Subject Classification ID

Medical applications (general) (92C50) Time series analysis of dynamical systems (37M10) Computational methods for problems pertaining to biology (92-08)

Related Items (1)

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques

Cites Work

• On an improved model reduction technique for nonlinear systems
• Comparison of Different Methods for Computing Lyapunov Exponents
• A prediction-error and stepwise-regression estimation algorithm for non-linear systems
• VALIDATING IDENTIFIED NONLINEAR MODELS WITH CHAOTIC DYNAMICS
• A new look at the statistical model identification

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