A Method for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise Using Extended Kalman Filter

DOI10.1007/978-3-642-28926-2_25zbMath1494.62017OpenAlexW2109154332WikidataQ58143114 ScholiaQ58143114MaRDI QIDQ5867228

Kamalanand Krishnamurthy

Publication date: 13 September 2022

Published in: Mathematical Modelling and Scientific Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-28926-2_25

zbMATH Keywords

neural networksLyapunov exponentsextended Kalman filterchaos theory

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Cites Work

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• Chaotic time series analyses of epileptic seizures
• Determining Lyapunov exponents from a time series
• A practical method for calculating largest Lyapunov exponents from small data sets
• Estimating the Lyapunov Exponent of a Chaotic System With Nonparametric Regression
• Ergodic theory of chaos and strange attractors

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