The main purpose of this work is to characterize the almost sure local structure stability of solutions to a class of linear stochastic partial functional differential equations (SPFDEs) by investigating the Lyapunov exponents and invariant manifolds near the stationary point. It is firstly proved that the trajectory field of the stochastic delayed stochastic partial functional differential equation admits an almost sure continuous version which is compact for $t>\tau$ by a delicate construction based on the random semiflow generated by the diffusion term. Then it is proved that the version generates a random dynamical system(RDS) by the Wong-Zakai approximation of the stochastic partial differential equation constructed by the diffusion te...
Invariant manifolds provide the geometric structures for describing and understanding dynamics of no...
AbstractWe state and prove a Local Stable Manifold Theorem (Theorem 4.1) for non-linear stochastic d...
Random invariant manifolds provide geometric structures for understanding stochastic dynamics. In th...
Abstract: "We consider a class of stochastic linear functional differential systems driven by semima...
The main objective of the talk is to characterize the pathwise local structure of solutions of semil...
We give several examples and examine case studies of linear stochastic functional differential equat...
This first volume is concerned with the analytic derivation of explicit formulas for the leading-ord...
AbstractIn this paper, we consider a class of stochastic partial differential equations (SPDEs) driv...
In this monograph, we investigate the long-time behavior of stochastic delay equations. Our approach...
A lot of works has been devoted to stability analysis of a stationary point for linear and non-linea...
This article is a sequel to [M.Z.Z.1] aimed at completing the characterization of the pathwise local...
The main objective of this work is to characterize the pathwise local structure of solutions of semi...
Building on results obtained in [21], we prove Local Stable and Unstable Manifold Theorems for nonli...
The objective of this paper is to use the Lyapunov function to study the almost sure exponential sta...
This thesis examines the asymptotic behaviour of solution flows of certain stochastic differential e...
Invariant manifolds provide the geometric structures for describing and understanding dynamics of no...
AbstractWe state and prove a Local Stable Manifold Theorem (Theorem 4.1) for non-linear stochastic d...
Random invariant manifolds provide geometric structures for understanding stochastic dynamics. In th...
Abstract: "We consider a class of stochastic linear functional differential systems driven by semima...
The main objective of the talk is to characterize the pathwise local structure of solutions of semil...
We give several examples and examine case studies of linear stochastic functional differential equat...
This first volume is concerned with the analytic derivation of explicit formulas for the leading-ord...
AbstractIn this paper, we consider a class of stochastic partial differential equations (SPDEs) driv...
In this monograph, we investigate the long-time behavior of stochastic delay equations. Our approach...
A lot of works has been devoted to stability analysis of a stationary point for linear and non-linea...
This article is a sequel to [M.Z.Z.1] aimed at completing the characterization of the pathwise local...
The main objective of this work is to characterize the pathwise local structure of solutions of semi...
Building on results obtained in [21], we prove Local Stable and Unstable Manifold Theorems for nonli...
The objective of this paper is to use the Lyapunov function to study the almost sure exponential sta...
This thesis examines the asymptotic behaviour of solution flows of certain stochastic differential e...
Invariant manifolds provide the geometric structures for describing and understanding dynamics of no...
AbstractWe state and prove a Local Stable Manifold Theorem (Theorem 4.1) for non-linear stochastic d...
Random invariant manifolds provide geometric structures for understanding stochastic dynamics. In th...