Stability of stochastic differential equations in manifolds
Stability of stochastic processes defined by integral functionals
The paper is devoted to the study of integral functionals for continuous nonincreasing functions f and nonnegative stochastic processes X(t,ω) with stationary and independent increments. In particular, a concept of stability defined in terms of the functionals with a ∈ (0,∞) is discussed.
Stability of stochastic reaction-diffusion recurrent neural networks with unbounded distributed delays.
Stability of the positive point of equilibrium of Nicholson's blowflies equation with stochastic perturbations: numerical analysis.
Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback
In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...
Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback
In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...
Stabilization of partially linear composite stochastic systems via stochastic Luenberger observers
The present paper addresses the problem of the stabilization (in the sense of exponential stability in mean square) of partially linear composite stochastic systems by means of a stochastic observer. We propose sufficient conditions for the existence of a linear feedback law depending on an estimation given by a stochastic Luenberger observer which stabilizes the system at its equilibrium state. The novelty in our approach is that all the state variables but the output can be corrupted by noises...
Stabilization of Volterra equations by noise.
Stable convergence of generalized stochastic integrals and the principle of conditioning.
State tameness: a new approach for credit constrains.
Static hedging of barrier options with a smile : an inverse problem
Let be a parabolic second order differential operator on the domain Given a function and such that the support of is contained in , we let be the solution to the equation:Given positive bounds we seek a function with support in such that the corresponding solution satisfies:We prove in this article that, under some regularity conditions on the coefficients of continuous solutions are unique and dense in the sense that can be -approximated, but an exact solution does not...
Static Hedging of Barrier Options with a Smile: An Inverse Problem
Let L be a parabolic second order differential operator on the domain Given a function and such that the support of û is contained in , we let be the solution to the equation: Given positive bounds we seek a function u with support in such that the corresponding solution y satisfies: We prove in this article that, under some regularity conditions on the coefficients of L, continuous solutions are unique and dense in the sense that can be C0-approximated, but an exact solution...
Stationary distributions for jump processes with memory
We analyze a jump processes with a jump measure determined by a “memory” process . The state space of is the Cartesian product of the unit circle and the real line. We prove that the stationary distribution of is the product of the uniform probability measure and a Gaussian distribution.
Stationary Quantum Markov processes as solutions of stochastic differential equations
From the operator algebraic approach to stationary (quantum) Markov processes there has emerged an axiomatic definition of quantum white noise. The role of Brownian motion is played by an additive cocycle with respect to its time evolution. In this report we describe some recent work, showing that this general structure already allows a rich theory of stochastic integration and stochastic differential equations. In particular, if a quantum Markov process is represented by a unitary cocycle, we can...
Stationary solutions for heat equation perturbed by general additive noise.
Statistical causality and adapted distribution
In the paper D. Hoover, J. Keisler: Adapted probability distributions, Trans. Amer. Math. Soc. 286 (1984), 159–201 the notion of adapted distribution of two stochastic processes was introduced, which in a way represents the notion of equivalence of those processes. This very important property is hard to prove directly, so we continue the work of Keisler and Hoover in finding sufficient conditions for two stochastic processes to have the same adapted distribution. For this purpose we use the concept...
Statistical inference for stochastic parabolic equations: a spectral approach.
Stetige stochastische Approximation.
Stochastic affine evolution equations with multiplicative fractional noise
A stochastic affine evolution equation with bilinear noise term is studied, where the driving process is a real-valued fractional Brownian motion with Hurst parameter greater than . Stochastic integration is understood in the Skorokhod sense. The existence and uniqueness of weak solution is proved and some results on the large time dynamics are obtained.