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arXiv 2101.09396nlin.CD
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混沌映射中的符号划分

Symbolic partition in chaotic maps

Misha Chai, Yueheng Lan

AI总结:

本文提出仅利用不稳定流形数据,通过检查不同层级折叠点(与同宿切点重合)来定位混沌映射符号划分边界的方法,并在二维和三维映射中验证了其有效性。

摘要:

在本研究中,我们仅利用不稳定流形的数据,通过检查不同层级的折叠点来定位划分边界,这些折叠点实际上与同宿切点(HTs)重合。该方法随后被应用于经典的二维Henon映射和一著名的三维映射。在Henon情形中与先前结果进行了比较,并基于该划分通过度量熵计算了Lyapunov指数,以证明当前方案的有效性。

英文摘要:

In this work, we only use data on the unstable manifold to locate the partition boundaries by checking folding points at different levels, which practically coincide with homoclinic tangencies (HTs). The method is then applied to the classic two-dimensional Henon map and a well-known three-dimensional map. Comparison with previous results is made in the Henon case and Lyapunov exponents are computed through the metric entropy based on the partition, to show the validity of the current scheme.

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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