An Optimization Approach for Finding a Spectrum of Lyapunov Exponents

  • Panos M. Pardalos
  • Vitaliy A. Yatsenko
  • Alexandre Messo
  • Altannar Chinchuluun
  • Petros Xanthopoulos
Part of the Springer Optimization and Its Applications book series (SOIA, volume 38)


In this chapter, we consider an optimization technique for estimating the Lyapunov exponents from nonlinear chaotic systems. We then describe an algorithm for solving the optimization model and discuss the computational aspects of the proposed algorithm. To show the efficiency of the algorithm, we apply it to some well-known data sets. Numerical tests show that the algorithm is robust and quite effective, and its performance is comparable with that of other well-known algorithms.


Lyapunov Exponent Temporal Lobe Epilepsy Strange Attractor Lorenz System Large Lyapunov Exponent 
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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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Industrial and Systems Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA
  2. 2.Department of OptimizationKungliga Tekniska HögskolanStockholmSweden

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