论文标题
动态离散网络与动态的布朗尼网络的收敛
Convergence of the dynamical discrete web to the dynamical Brownian web
论文作者
论文摘要
在本文中，我们研究了动力学离散网（DYDW）与路径空间拓扑中动力学的布朗尼网络（DYBW）的收敛。我们表明，几乎可以肯定的是，DYBW的RCLL路径在适当的度量空间中采用值，并且作为一系列RCLL路径，缩放的动态离散Web会收敛到DYBW。这证明了DYDW过程与DYBW工艺的融合较弱。
In this paper we study the convergence of dynamical discrete web (DyDW) to the dynamical Brownian web (DyBW) in the path space topology. We show that almost surely the DyBW has RCLL paths taking values in an appropriate metric space and as a sequence of RCLL paths, the scaled dynamical discrete web converges to the DyBW. This proves weak convergence of the DyDW process to the DyBW process.
