Recursive prediction of chaotic time series

DOI10.1007/BF02429864zbMath0798.65133OpenAlexW2012144015MaRDI QIDQ1322783

Jaroslav Stark

Publication date: 20 October 1994

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

Full work available at URL: https://doi.org/10.1007/bf02429864

zbMATH Keywords

numerical stabilitychaotic systemstime series predictionrecursive least squares methodsradial basis approximationorthogonal methodexponential divergence of trajectoriesHenon map systemrecursive modified Gram-Schmidt methods

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12) Probabilistic methods, stochastic differential equations (65C99)

Related Items (5)

Jaroslav Stark: 1960–2010 ⋮ Predicting chaotic time series with wavelet networks ⋮ Invariant graphs for forced systems ⋮ Predicting economic time series using a nonlinear deterministic technique ⋮ Recurrence plots revisited

Cites Work

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• Recursive estimation and time-series analysis. An introduction
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• Embedology
• Variation of Lyapunov exponents on a strange attractor
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• Independent coordinates for strange attractors from mutual information
• EXTRACTING SLOWLY VARYING SIGNALS FROM A CHAOTIC BACKGROUND
• NONLINEAR TIME SEQUENCE ANALYSIS
• THE TAKENS EMBEDDING THEOREM
• Ergodic theory of chaos and strange attractors
• Updating the singular value decomposition

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