Empirical evaluated SDE modelling for dimensionality-reduced systems and its predictability estimates
DOI10.1007/S13160-017-0296-2zbMath1404.60054OpenAlexW2792949031MaRDI QIDQ1756720
Seiichiro Kusuoka, Masaru Inatsu, Yoshitaka Saiki, Naoto Nakano
Publication date: 21 December 2018
Published in: Japan Journal of Industrial and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13160-017-0296-2
stochastic differential equationinverse problemnonlinear dynamical systemspredictabilitydimensionality reduction
Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Prediction theory (aspects of stochastic processes) (60G25)
Cites Work
- Fast chaos versus white noise: Entropy analysis and a Fokker-Planck model for the slow dynamics
- Quantifying local predictability in phase space
- The Fokker-Planck equation. Methods of solution and applications.
- Elimination of fast chaotic degrees of freedom: on the accuracy of the Born approximation
- Dependent central limit theorems and invariance principles
- A note on estimating drift and diffusion parameters from time series
- Analysis of data sets of stochastic systems
- Stochastic modelling: replacing fast degrees of freedom by noise
- Stochastic modelling of intermittency
- Evaluation of Mean Values for a Forced Pendulum with a Projection Operator Method
- Transport, Collective Motion, and Brownian Motion
- Turbulence, Coherent Structures, Dynamical Systems and Symmetry
This page was built for publication: Empirical evaluated SDE modelling for dimensionality-reduced systems and its predictability estimates