Time series analysis for system identification and diagnostics

DOI10.1016/0167-2789(91)90059-IzbMath0717.92002OpenAlexW2064624064MaRDI QIDQ2638980

Polina S. Landa, Michael G. Rosenblum

Publication date: 1991

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-2789(91)90059-i

zbMATH Keywords

noisechaotic motionLyapunov exponentmodel fittingTakens theoremprediction of time seriesdynamical system diagnosticsestimation of attractor dimensioninhomogeneous attractorsiterative filtering algorithmphase space constructionself-generated oscillations

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) General biology and biomathematics (92B05) Computational methods for problems pertaining to biology (92-08)

Related Items (5)

Experimental nonlinear physics ⋮ On-off intermittency phenomena in a pendulum with a randomly vibrating suspension axis ⋮ On possible inaccuracy in quantification of chaotic motion ⋮ Blind Extraction of Chaotic Sources from White Gaussian Noise Based on a Measure of Determinism ⋮ Local Lyapunov exponents computed from observed data

Cites Work

• Reconstructing attractors from scalar time series: A comparison of singular system and redundancy criteria
• Chaotic attractors of an infinite-dimensional dynamical system
• Extracting qualitative dynamics from experimental data
• Finite correlation dimension for stochastic systems with power-law spectra
• An equation for continuous chaos
• Independent coordinates for strange attractors from mutual information
• Oscillation and Chaos in Physiological Control Systems
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