Perkins, E. (1994). The strong Markov property of the support of super-Brownian motion. The Dynkin Festschrift. Progr. Probab. 24 307-326. Birkh¨auser, Boston, MA.E. Perkins (1994). The Strong Markov Property of the Support of Super-Brownain Motion. In: The Dynkin Festschrift ...
Strong Markov Property, Skorokhod Embedding, and Donsker’s Invariance PrincipleThis chapter ties together a number of the topics introduced in the text via applications to the further analysis of Brownian motion, a fundamentally important stochastic process whose existence was established in Chapter IX....
asymptotic equipartition propertyAEP/ A0540 Fluctuation phenomena, random processes, and Brownian motion A0250 Probability theory, stochastic processes, and statisticsIn this paper, we are going to study the strong laws of large numbers for asymptotic even–odd Markov chains indexed by a homogeneous ...
A result of the general theory for affine Markov processes on the cone Sd+ of symmetric positive semidefinite matrices developed in [13] is that for a d×d matrix-valued standard Brownian motion B, d×d matrices Q and β, a symmetric constant drift b, and a positive linear drift Γ:Sd...
right-continuous with finite left-hand limits, versions and it is a routine argument that the Feller (or Cb-Feller) property of the semigroup together with the Markov property entail the strong Markov property of the process. As usual, Ttu(x) = Ex(u(Xt)), u ∈ C∞(Rd), t ≥ 0,...
Strong Markov propertyStochastic differential equationsG-Brownian motionReflection principleThe objective of this paper is to study the strong Markov property for the stochastic differential equations driven by G-Brownian motion (G-SDEs for short). We first extend the deterministic-time conditional G-...
We study the mixing properties of an important optimization algorithm of machine learning: the stochastic gradient Langevin dynamics (SGLD) with a fixed step size. The data stream is not assumed to be independent hence the SGLD is not a Markov chain, merely a Markov chain in a random environme...
The theory of the averaging principle has a long and rich history. Let us mention a few of them. Khasminskii [] first proved the averaging principle of stochastic differential equa- tions (SDEs) driven by Brownian noise. Since then, the averaging principle has been an active research ...
Strong Markov propertyStochastic differential equationsG -Brownian motionReflection principleThe objective of this paper is to study the strong Markov property for the stochastic differential equations driven by G-Brownian motion (G-SDEs for short). We first extend the deterministic-time conditional G-...
1) strong Markov property of Brownian motion 布朗运动的强马尔可夫性2) strong Markov property 强马尔可夫性 1. The paper proofs that the hitting time is a stopping time on general set of state space of homogeneous Markov chain,the corresponding sequence is still a homogeneous Markov chain with ...