Stochastic averaging principle for two-time-scale jump-diffusion SDEs under the non-Lipschitz coefficients
DOI10.1080/17442508.2020.1784897zbMath1496.60067OpenAlexW3041673357MaRDI QIDQ5086701
Publication date: 7 July 2022
Published in: Stochastics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/17442508.2020.1784897
existence and uniquenessnon-Lipschitz coefficientsstochastic averaging principlefast-slow SDEs with jumps\(L^2\)-strong convergence
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Systems with slow and fast motions for nonlinear problems in mechanics (70K70) Averaging of perturbations for nonlinear problems in mechanics (70K65)
Cites Work
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- Strong convergence of principle of averaging for multiscale stochastic dynamical systems
- Strong convergence rate of principle of averaging for jump-diffusion processes
- \(L^p(p > 2)\)-strong convergence of an averaging principle for two-time-scales jump-diffusion stochastic differential equations
- Stochastic averaging: An approximate method of solving random vibration problems
- On a type of stochastic differential equations driven by countably many Brownian motions
- Random perturbation methods with applications in science and engineering
- Computational singular perturbation analysis of stochastic chemical systems with stiffness
- Jump type stochastic differential equations with non-Lipschitz coefficients: non-confluence, Feller and strong Feller properties, and exponential ergodicity
- Stochastic averaging for two-time-scale stochastic partial differential equations with fractional Brownian motion
- Strong averaging principle for two-time-scale SDEs with non-Lipschitz coefficients
- On the uniqueness of solutions of stochastic differential equations
- Stochastic Averaging in Discrete Time and its Applications to Extremum Seeking
- Continuous-Time Stochastic Averaging on the Infinite Interval for Locally Lipschitz Systems
- Multiscale Integration Schemes for Jump-Diffusion Systems
- ON THE AVERAGING PRINCIPLE FOR SYSTEMS OF STOCHASTIC DIFFERENTIAL EQUATIONS
- Strong Convergence Rate for Two-Time-Scale Jump-Diffusion Stochastic Differential Systems
- Stability and Control of Stochastic Systems with Wide-band Noise Disturbances. I
- Averaging principle for diffusion processes
- Introduction to Stochastic Search and Optimization
- STOCHASTIC VERSIONS OF ANOSOV'S AND NEISTADT'S THEOREMS ON AVERAGING
- Stochastic Averaging in Continuous Time and Its Applications to Extremum Seeking
- An averaging principle for a completely integrable stochastic Hamiltonian system
- Analysis of multiscale methods for stochastic differential equations
- Averaging methods in nonlinear dynamical systems
- Stochastic differential equations. An introduction with applications.
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