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  • 标题:Koopman Operator Methods for Global Phase Space Exploration of Equivariant Dynamical Systems ⁎
  • 本地全文:下载
  • 作者:Subhrajit Sinha ; Sai Pushpak Nandanoori ; Enoch Yeung
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:1150-1155
  • DOI:10.1016/j.ifacol.2020.12.1322
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, we develop the Koopman operator theory for dynamical systems with symmetry. In particular, we investigate how the Koopman operator and eigenfunctions behave under the action of the symmetry group of the underlying dynamical system. Further, exploring the underlying symmetry, we propose an algorithm to construct a global Koopman operator from local Koopman operators. In particular, we show, by exploiting the symmetry, data from all the invariant sets are not required for constructing the global Koopman operator; that is, local knowledge of the system is enough to infer the global dynamics.
  • 关键词:KeywordsDynamic systemsOperatorsLearning algorithmsEquivariant systemsKoopman operatorsData-driven analysis
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