通过弗里曼曲线编码和分析进行轨迹分类
Roxana Peña-Mendieta1, Ania Mesa-Rodríguez1,2, Daniel Estevez-Moya2,3
1Facultad de Matemática y Computación, Universidad de La Habana, La Habana, Cuba.
PloS one
|November 4, 2025
概括
本研究使用对它们编码表示的分析来对二维轨迹进行分类. 这种方法利用科尔莫戈罗夫-西奈,有效地分类复杂的运动模式,如海农-海尔斯模型和人类姿势.
科学领域:
- 动态系统和复杂性科学 动态系统和复杂性科学
- 信息理论 信息理论
- 计算物理 计算物理
背景情况:
- 轨迹分析对于理解复杂系统至关重要.
- 传统方法可能会在高维或噪音数据方面扎.
- 描述运动模式需要强大的定量测量.
研究的目的:
- 开发一种用于分类二维轨迹的新方法.
- 将分析应用于编码的轨迹表示.
- 用各种例子来证明该方法的多功能性.
主要方法:
- 使用弗里曼程序将轨迹分离成一个8符号的代码.
- 应用分析,包括科尔摩戈罗夫-西奈.
- 利用有效的复杂性和信息距离措施.
- 开发基于变量的分类方案.
主要成果:
- 编码轨迹的分析提供了一个强大的分类框架.
- 亨农-海尔斯模型被成功分类,验证了该方法的复杂性分析能力.
- 分析了人体姿势数据,显示了该方法对现实世界的实验数据的适用性.
结论:
- 拟议的编码轨迹的分析为轨迹分类提供了一个强大的工具.
- 这种方法可以适应各种复杂的系统,从理论模型到实验数据.
- 这种方法有助于区分和理解不同的运动动态.
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