Extracting governing laws from sample path data of non-Gaussian stochastic dynamical systems

DOI10.1007/s10955-022-02873-yzbMath1490.60114arXiv2107.10127OpenAlexW3183862791MaRDI QIDQ2076049

Yang Li, Jin-qiao Duan

Publication date: 18 February 2022

Published in: Journal of Statistical Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2107.10127

zbMATH Keywords

rare eventsnon-Gaussian Lévy noisestochastic dynamical systemsheavy-tailed fluctuationsnonlocal Kramers-Moyal formulas

Mathematics Subject Classification ID

Processes with independent increments; Lévy processes (60G51) Probabilistic models, generic numerical methods in probability and statistics (65C20) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Generation, random and stochastic difference and differential equations (37H10) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (5)

Data-driven approximation for extracting the transition dynamics of a genetic regulatory network with non-Gaussian Lévy noise ⋮ Extracting stochastic dynamical systems with α-stable Lévy noise from data ⋮ Learning mean-field equations from particle data using WSINDy ⋮ Stochastic dynamics and data science ⋮ Data-driven method to extract mean exit time and escape probability for dynamical systems driven by Lévy noises

Uses Software

• GitHub

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Discovering governing equations from data by sparse identification of nonlinear dynamical systems
• Lévy flights in evolutionary ecology
• A data-driven approximation of the koopman operator: extending dynamic mode decomposition
• Analysis of a delayed vaccinated SIR epidemic model with temporary immunity and Lévy jumps
• Data-driven approximation of the Koopman generator: model reduction, system identification, and control
• A data-driven approach for discovering stochastic dynamical systems with non-Gaussian Lévy noise
• Most probable transition pathways and maximal likely trajectories in a genetic regulatory system
• Effects of Lévy noise on the Fitzhugh-Nagumo model: a perspective on the maximal likely trajectories
• Fluctuations of Lévy processes with applications. Introductory lectures
• Mean Exit Time and Escape Probability for Dynamical Systems Driven by Lévy Noises
• Effects of Lévy noise on the dynamics of sine-Gordon solitons in long Josephson junctions
• Spectral characteristics of steady-state Lévy flights in confinement potential profiles
• Lévy noise-induced escape in an excitable system
• Lévy Processes and Stochastic Calculus
• Stochastic basins of attraction for metastable states
• Lévy noise induced transition and enhanced stability in a gene regulatory network
• Financial Modelling with Jump Processes
• Governing equations for probability densities of Marcus stochastic differential equations with Lévy noise
• Most probable dynamics of stochastic dynamical systems with exponentially light jump fluctuations
• Discovering transition phenomena from data of stochastic dynamical systems with Lévy noise
• Extracting non-Gaussian governing laws from data on mean exit time
• Detecting the maximum likelihood transition path from data of stochastic dynamical systems
• Sparse dynamics for partial differential equations
• The maximum likelihood climate change for global warming under the influence of greenhouse effect and Lévy noise
• Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems
• Discovering mean residence time and escape probability from data of stochastic dynamical systems
• Stochastic Dynamics of Two Picophytoplankton Populations in a Real Marine Ecosystem
• Data-Driven Identification of Parametric Partial Differential Equations

This page was built for publication: Extracting governing laws from sample path data of non-Gaussian stochastic dynamical systems