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arXiv 2301.06753math.DS
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检验时间序列的拓扑共轭性

Testing topological conjugacy of time series

Paweł Dłotko, Michał Lipiński, Justyna Signerska-Rynkowska

AI总结:

提出基于有限轨道样本和给定映射检验两个动力系统是否拓扑共轭的方法,证明渐近收敛性,并用于 Takens 嵌入维数与时间序列相似性检验。

摘要:

本文考虑从有限样本出发检验两个动力系统 $(X,f)$ 与 $(Y,g)$ 是否拓扑共轭的问题。更具体地说,给定 $x_1,\ldots,x_n\subset X$ 和 $y_1,\ldots,y_n\subset Y$,满足 $x_{i+1}=f(x_i)$ 与 $y_{i+1}=g(y_i)$,并给定映射 $h:X\rightarrow Y$,我们提出若干检验,以判断 $f$ 与 $g$ 是否通过 $h$ 拓扑共轭。对于共轭系统,这些检验的数值接近零;对于非共轭系统,数值则较大。文中证明了当样本量趋于无穷大时检验值的收敛性。文中还给出了若干数值例子,表明这些方法具有可扩展性和稳健性。此外,我们展示了所提方法如何特化为 Takens 嵌入定理中充分嵌入维数的检验。我们的方法也适用于给定确定性过程的两个观测量的情形,这些观测量以一维或高维时间序列的形式给出。在此情况下,可以通过比较其 Takens 重构的动力学来评估它们的相似性。

英文摘要:

This paper considers a problem of testing, from a finite sample, a topological conjugacy of two dynamical systems $(X,f)$ and $(Y,g)$. More precisely, given $x_1,\ldots, x_n \subset X$ and $y_1,\ldots,y_n \subset Y$ such that $x_{i+1} = f(x_i)$ and $y_{i+1} = g(y_i)$ as well as $h: X \rightarrow Y$, we deliver a number of tests to check if $f$ and $g$ are topologically conjugated via $h$. The values of the tests are close to zero for conjugated systems and large for systems that are not conjugated. Convergence of the test values, in case when sample size goes to infinity, is established. A number of numerical examples indicating scalability and robustness of the methods are given. In addition, we show how the presented method specialize to a test of sufficient embedding dimension in Takens' embedding theorem. Our methods also apply to the situation when we are given two observables of deterministic processes, of a form of one or higher dimensional time-series. In this case, their similarity can be accessed by comparing the dynamics of their Takens' reconstructions.

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。

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