Chaos pp 149-187 | Cite as

Reconstruction of Dynamics from Observables

  • Anastasios A. Tsonis


The study of the mathematical dynamical systems presented in the previous chapters advanced our understanding of the dynamics of nonlinear deterministic systems. We now know that random-looking behavior can arise from simple nonlinear systems. Such dynamics, now termed chaotic dynamics, exhibit complicated strange attractors that are fractal sets with positive Lyapunov exponents. We also learned how the dynamic behavior of a system can change via bifurcations, and how period doubling, intermittency, and crisis can take a system from a periodic to a nonperiodic evolution.


Mutual Information Lyapunov Exponent Correlation Dimension Embedding Dimension Capacity Dimension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Anastasios A. Tsonis
    • 1
  1. 1.University of Wisconsin at MilwaukeeMilwaukeeUSA

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