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.

以马里兰大学为中心的一组研究人员将参与混沌动力系统的数学和物理研究，特别包括通过嵌入方法重建吸引子的基本问题，以及通过嵌入方法恢复动力学，这对于混沌动力学系统的研究至关重要。使该方法对实验数据有用。 其他需要研究的领域是混沌瞬态和计算机生成的非线性过程轨迹的严格验证。 重点将放在开发用于分析实验数据的计算机算法。 过去十年来，混沌和混沌行为的研究引起了人们的关注，理论家和实验家之间有大量令人兴奋的互动机会，从而可以将新的理论理解转移到实验室。