arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2409.06003math.PRmath.DS
收藏

关于某些 Lipschitz 数为一的随机函数迭代的研究

On the iterations of some random functions with Lipschitz number one

Yingdong Lu, Tomasz Nowicki

AI总结:

本文研究 Lipschitz 数为一的随机映射迭代,将其建模为 Markov 链,证明温和条件下的收敛性与 Wasserstein 度量非扩张性及多项式速率条件,并刻画相关非线性算子的不动点。

摘要:

针对映射 $x\mapsto|x-θ|$ 这类 Lipschitz 数为一的随机函数的迭代,我们将其动力学表示为一条 Markov 链,并在温和条件下证明了它的收敛性。我们还证明,任意两个测度经过相应诱导的测度迭代后,其 Wasserstein 度量不会增加,并确定了在该度量下可获得多项式收敛速率的条件。我们还考虑了概率测度空间上的一个相关非线性算子,并通过对其特征函数的详细分析确定了其不动点。

英文摘要:

For the iterations of $x\mapsto |x-θ|$ random functions with Lipschitz number one, we represent the dynamics as a Markov chain and prove its convergence under mild conditions. We also demonstrate that the Wasserstein metric of any two measures will not increase after the corresponding induced iterations for measures and identify conditions under which a polynomial convergence rate can be achieved in this metric. We also consider an associated nonlinear operator on the space of probability measures and identify its fixed points through an detailed analysis of their characteristic functions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑