分数顺序系统的识别方法,以同等动态属性来表示
Minjuan Yuan1, Wei Xu1, Fawang Liu2,3
1Department of Applied Probability and Statistics, School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an, Shaanxi 710129, China.
Chaos (Woodbury, N.Y.)
|July 9, 2024
概括
本研究提出了一种新的方法,用于识别使用稀疏回归的分数动态系统. 该方法创建了等价的整数顺序方程,这些方程捕捉了原始系统的动态属性,而没有内存条款.
科学领域:
- 动态系统 动态系统
- 控制理论 控制理论
- 应用数学 应用数学 应用数学
背景情况:
- 分数动态系统提供复杂的行为,但很难识别.
- 传统的方法侧重于分数项的计算效率.
- 需要基于数据的方法来识别分数系统.
研究的目的:
- 开发一种高效,数据驱动的方法来识别分数动态系统.
- 构建相当的整数顺序模型,保留原始系统的动态.
- 将分数顺序视为可变量,用于强大的动态属性捕获.
主要方法:
- 使用扩展稀疏回归来将数据与候选函数相匹配.
- 使用交叉验证来选择最准确和最节的方程.
- 在识别过程中将分数顺序视为变量.
主要成果:
- 识别的最佳方程准确地代表了分数系统的动态.
- 相当的模型成功地捕捉了不同分数顺序的动态行为.
- 识别的系统表现出随机的P-分叉现象,类似于原始的分数系统,没有非局部术语.
结论:
- 拟议的方法提供了一种有效的方法,可以从数据中识别分数动态系统.
- 相当的整数顺序模型可以复制复杂的动态,包括P-分叉,没有内存.
- 这种以数据为中心的方法为分析和建模分数系统提供了新的视角.
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