Modelling Dynamical Systems from Real-World Data

  • Alistair Mees
Part of the NATO ASI Series book series (NSSB, volume 208)


This summary describes some of my work on construction of dynamical system models from data, as part of a larger project to identify nonlinear dynamics and distinguish it from noise. In the space available it is only possible to look briefly at a number of different ideas and applications. The reader is referred to the bibliography for fuller details.


Lyapunov Exponent Dynamical System Model Multivariate Adaptive Regression Spline Chaotic Time Series Modelling Complex System 
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  1. A. Bowyer, Computing Dirichlet tesselations, The Computer Journal, 24 (2), 162–166 (1981).MathSciNetCrossRefGoogle Scholar
  2. M. Casdagli, Phys. Rev. Letters, to appear (1989).Google Scholar
  3. J.D. Farmer and J.J. Sidorowich, Predicting chaotic time series, Phys. Rev. Letters 59 (8), 845–848 (1987).MathSciNetCrossRefGoogle Scholar
  4. J.H. Friedman, Multivariate adaptive regression splines, Technical Report 102, Laboratory for Computational Statistics, Stanford University (1988).Google Scholar
  5. A.I. Mees, Modelling Complex Systems, Proceedings of the Conference on Modelling Complex Systems, eds. L.S. Jennings, A.I. Mees and T.L. Vincent, Birkhauser-Boston (1989).Google Scholar

Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • Alistair Mees
    • 1
  1. 1.Mathematics DepartmentThe University of Western AustraliaAustralia

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