估计碎形尺寸:一个比较的审查和开源实现.
George Datseris1, Inga Kottlarz2,3,4, Anton P Braun2,4
1Department of Mathematics and Statistics, University of Exeter, EX4 4QF Exeter, United Kingdom.
Chaos (Woodbury, N.Y.)
|October 13, 2023
概括
在非线性动态学中,估计碎形维度至关重要. 对于无噪声数据,相关性总和优越,但对于现实数据,和极端价值理论对噪声更为坚固.
科学领域:
- 非线性动力学是一种非线性动力学.
- 复杂系统分析 复杂系统分析
- 数据科学数据科学数据科学
背景情况:
- 分形维度量化了动态系统中的复杂性.
- 为了估计碎形尺寸,存在各种数值技术.
- 需要对这些估计器进行全面的审查和评估.
研究的目的:
- 为了提供一个独立的介绍,以碎形维度估计.
- 评估和比较关键数值估计器的性能.
- 评估数据特征对估计器精度的影响.
主要方法:
- 对数值技术的审查,以估计碎形维度.
- 专注于通用,相关性和和极端价值理论.
- 使用合成和真实实验数据集进行定量评估.
主要成果:
- 相关性总和对于合成的无噪声数据是最优的.
- 对实验数据来说,和极端价值理论对噪声更有弹性.
- 极端价值理论可能会为不适当的数据产生虚假的低维结果.
结论:
- 分形维度估计器的选择取决于数据特征 (例如噪声).
- 极端价值理论显示出前景,但需要对现实世界的应用进行仔细验证.
- 对于讨论的算法,有开源实现可用.
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