一个混乱的同步诊断:时间序列差异峰值复杂性 (DTSPC)
Zhe Lin1, Arjendu K Pattanayak2
1United World College Changshu China, Suzhou 215500, China.
Entropy (Basel, Switzerland)
|January 8, 2025
概括
我们开发了一个新的算法,差异时间序列峰值复杂性 (DTSPC),以量化混乱同步. 该方法分析时间序列数据中的峰值模式,以区分各种同步行为,为理解复杂动态提供一种新的方法.
科学领域:
- 复杂系统科学 复杂系统科学
- 非线性动力学是一种非线性动力学.
- 混沌理论 混沌理论
背景情况:
- 混乱系统显示出对初始条件的敏感依赖,但可以通过合同步.
- 现有的同步分析方法通常依赖于相位轨迹,掩盖不同的行为并要求微分方程.
- 需要使用定量方法来区分混乱系统中的多种同步模式.
研究的目的:
- 介绍一个新的算法,差异时间序列峰值复杂性 (DTSPC),用于量化混乱同步.
- 用时间序列峰值模式的热分析来区分各种同步行为.
- 为了证明算法的有效性,捕捉复杂的同步动态和过渡行为.
主要方法:
- 开发差异时间序列峰值复杂度 (DTSPC) 算法.
- 利用来测量采样时间序列中峰值模式的复杂性.
- 专注于区别时间序列中的响声模式,以确定同步模式.
- 适用于各种参数的合洛伦兹系统 (相同和非相同).
主要成果:
- DTSPC算法成功量化了各种混乱同步行为.
- 该技术捕捉了非单调的关系和同步模式之间的复杂边界.
- 对合的洛伦茨系统的分析表明了算法的揭示过渡动态的能力.
结论:
- DTSPC算法为分析混沌同步复杂性提供了一个强大的定量测量方法.
- 这种热峰值模式分析有效地区分了不同的同步状态.
- 该方法为同步混乱系统中的过渡动态和各种行为提供了有价值的见解.
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