时间序列分析的简单复杂
Lev Guzmán-Vargas1, Alvaro Zabaleta-Ortega2, Aldo Guzmán-Sáenz3
1Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, 07340, Mexico City, Mexico. lguzmanv@ipn.mx.
Scientific reports
|December 20, 2023
概括
这项研究引入了一种新的度量,简化的复杂近似,以更好地描述复杂系统的动态. 该方法有效量化随机和混乱时间序列中的不规则性,并区分生理信号.
科学领域:
- 复杂性科学 复杂性科学
- 时间序列分析时间序列分析
- 非线性动力学是一种非线性动力学.
背景情况:
- 大自然中的复杂系统表现出动态行为,需要强大的分析方法.
- 现有的时间序列不规则度量与随机和混乱动态斗争.
- 需要新的方法来详细描述复杂系统动态.
研究的目的:
- 为了引入一种新的测量方法,简化复杂近似 (SCAE).
- 评估SCAE在各种复杂动态中表征不规则性的能力.
- 展示SCAE在区分生理状态和混乱系统方面的潜力.
主要方法:
- 开发了基于简单复杂元素的条件概率的简单复杂近似.
- 将SCAE应用于模拟的随机序列和低维混乱动态.
- 利用SCAE分析心跳间隔序列和合的混乱地图.
主要成果:
- SCAE提供了广泛的值,揭示了标准方法遗漏的细节.
- 该方法成功量化了随机和混乱时间序列中的不规则性.
- SCAE始终将心脏信号与健康和心力衰竭患者区分开来,并识别结合混沌地图中的变化.
结论:
- 简单复杂的近似提供了复杂系统动态的增强特征.
- 通过简化复合体揭示的结构对于详细分析至关重要.
- 这种方法对分析复杂系统的各种应用具有前景.
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