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Volumn 59, Issue 8, 1987, Pages 845-848

Predicting chaotic time series

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EID: 34249982739     PISSN: 00319007     EISSN: None     Source Type: Journal    
DOI: 10.1103/PhysRevLett.59.845     Document Type: Article
Times cited : (1559)

References (20)
  • 2
    • 84927433321 scopus 로고    scopus 로고
    • For example, S. M. Pandit and S.-M. Yu, Time Series and System Analysis with Applications (Wiley, New York, 1983).
  • 6
    • 84927433320 scopus 로고    scopus 로고
    • For example, G. Mayer-Kress, Dimensions and Entropies in Chaotic Systems (Springer-Verlag, Berlin, 1986).
  • 10
    • 84927433318 scopus 로고    scopus 로고
    • F. Takens, in Dynamical Systems and Turbulence, edited by D. A. Rand and L.-S. Young (Springer-Verlag, Berlin, 1981).
  • 18
    • 84927433316 scopus 로고    scopus 로고
    • Tmax is a crude estimate of our ability to forecast. In some cases E(T) reaches a plateau at a level less than 1. In these cases we estimate Tmax by extrapolating the initial rate of increase. (In some cases such as GL15 in Fig. 1, it is necessary to expand the T axis to see the initial increase.)
  • 19
    • 84927433314 scopus 로고    scopus 로고
    • Detailed arguments suggest that there may be a correction to the T scaling in Eq. (2), but we have not yet resolved this.
  • 20
    • 84927433312 scopus 로고    scopus 로고
    • ``Efficient algorithms with neural network behavior'' (to be published).
    • Omohundro, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.