Attractor Reconstruction from Experimental Data

根据实验数据重建吸引子

• 批准号: 9116391
• 负责人: James Yorke
• 金额: $ 37.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-04-01 至 1995-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9116391&HistoricalAwards=false
• 关键词: Attractor; Reconstruction; Experimental; Data

A group of researchers centered at the University of Maryland will be involved in mathematical and physical research on chaotic dynamical systems, including in particular foundational questions of attractor reconstruction through embedding methods, and the recovery of the dynamics through the embedding method, which is critical to making the approach useful for experimental data. Other areas to be investigated are chaotic transients and the rigorous verification of computer- generated trajectories of nonlinear processes. The focus will be on development of computer algorithms for the analysis of data from experiments. The study of chaos and chaotic behavior has attracted attention over the past decade, and there are substantial opportunities for exciting interactions between theoreticians and experimentalists, so that new theoretical understanding can be transferred to the laboratory.

一组研究人员集中在大学的 马里兰州将参与数学和物理研究 混沌动力系统，特别是 吸引子重构的基本问题 嵌入的方法，并通过恢复的动态 嵌入方法，这是使该方法有用的关键 实验数据。 其他有待调查的领域包括 混沌瞬态和计算机的严格验证， 生成非线性过程的轨迹。 将侧重 研究数据分析的计算机算法 从实验中。 混沌和混沌行为的研究吸引了 在过去的十年里，人们注意到， 理论家和科学家之间令人兴奋的互动机会， 实验主义者，这样新的理论理解就可以 转移到实验室。