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THE STATE SPACE RECONSTRUCTION TECHNOLOGY OF DIFFERENT KINDS OF CHAOTIC DATA OBTAINED FROM DYNAMICAL SYSTEM 被引量:4

THE STATE SPACE RECONSTRUCTION TECHNOLOGY OF DIFFERENT KINDS OF CHAOTIC DATA OBTAINED FROM DYNAMICAL SYSTEM
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摘要 Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail. Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail.
出处 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 1999年第1期82-92,共11页 力学学报(英文版)
基金 The project supported by the National Natural Science Foundation of China(19672043)
关键词 nonlinear chaotic data embedding space matrix eigenvalue and eigenvector state space reconstruction nonlinear chaotic data embedding space matrix eigenvalue and eigenvector state space reconstruction
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  • 1Potapov Alexei.Distortions of reconstruction for chaotic attractors[].Physica D Nonlinear Phenomena.1997 被引量:1
  • 2Judd Kevin,Mees Alistair.Embedding as a modeling problem[].Physica D Nonlinear Phenomena.1998 被引量:1
  • 3Kugiumtzis D,Lingjxrde O C,Christophersen N.Regularized local linear prediction of chaotic time series[].Physica D Nonlinear Phenomena.1998 被引量:1
  • 4Abarbanel Henry D I,Brown Reggie,Kadtke James B.Prediction and system identification in chaotic nonlinear systems: time series with broadband spectra[].Physics Letters A.1989 被引量:1
  • 5Schroer Christian G,Sauer Tim,Ott Edvard,et al.Predicting chaotic most of the time from embeddings with self_intersections[].Physical Review Letters.1998 被引量:1
  • 6CAO Liang_yue,HONG Yi_guang,FANG Hai_ping,et al.Predicting chaotic timeseries with wavelet networks[].Physica D Nonlinear Phenomena.1995 被引量:1
  • 7ZHANG Qing_hua.Wavelet networks[].IEE Transaction on Neural Networks.1992 被引量:1
  • 8Davies M E.Reconstructing attractors from filtered timeseries[].Physica D Nonlinear Phenomena.1997 被引量:1
  • 9Diambra L,Plastino A.Modeling time series using information theory[].Physics Letters A.1996 被引量:1
  • 10Chen C H.Applied Timeseries Analysis[]..1989 被引量:1

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