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An approach of parameter estimation for non-synchronous systems

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  • Xu, Daolin
  • Lu, Fangfang

Abstract

Synchronization-based parameter estimation is simple and effective but only available to synchronous systems. To come over this limitation, we propose a technique that the parameters of an unknown physical process (possibly a non-synchronous system) can be identified from a time series via a minimization procedure based on a synchronization control. The feasibility of this approach is illustrated in several chaotic systems.

Suggested Citation

  • Xu, Daolin & Lu, Fangfang, 2005. "An approach of parameter estimation for non-synchronous systems," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 361-366.
    • Handle: RePEc:eee:chsofr:v:25:y:2005:i:2:p:361-366
    DOI: 10.1016/j.chaos.2004.11.020
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    Cited by:

    1. He, Qie & Wang, Ling & Liu, Bo, 2007. "Parameter estimation for chaotic systems by particle swarm optimization," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 654-661.
    2. Peng, Bo & Liu, Bo & Zhang, Fu-Yi & Wang, Ling, 2009. "Differential evolution algorithm-based parameter estimation for chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2110-2118.
    3. Li, Chaoshun & Zhou, Jianzhong & Xiao, Jian & Xiao, Han, 2012. "Parameters identification of chaotic system by chaotic gravitational search algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 539-547.

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