Journal of Optimization Theory and Applications

, Volume 134, Issue 3, pp 533–547 | Cite as

Optimization in Control and Learning in Coupled Map Lattice Systems

  • S. P. Nair
  • P. M. Pardalos
  • V. A. Yatsenko


In this paper, we analyze various control algorithms that have been proposed for controlling spatiotemporal chaos in a globally coupled map lattice (CML) system. We reformulate the choice of feedback parameters in such systems as a constrained optimization problem and provide numerical and experimental results on the choice of optimal parameters for controlling the mean global Lyapunov exponent of a lattice. Finally, we propose a scheme to use this optimization technique to solve a learning problem in which such a CML system can be used to emulate the dynamics of an epileptic brain.


Optimization Control Lyapunov exponents Brain dynamics Seizure Lattice systems 


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© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department Biomedical EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Department Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  3. 3.Department of Space PlasmaInstitute of Space ResearchKievUkraine

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