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Parameter estimation of a delay dynamical system using synchronization in presence of noise

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  • Rakshit, Biswambhar
  • Chowdhury, A. Roy
  • Saha, Papri

Abstract

A method of parameter estimation of a time delay chaotic system through synchronization is discussed. It is assumed that the observed data can always be effected with some white Gaussian noise. A least square approach is used to derive a system of differential equations which governs the temporal evolution of the parameters. These system of equations together with the coupled delay dynamical systems, when integrated, leads to asymptotic convergence to the value of the parameter along with synchronization of the two system variables. This method is quite effective for estimating the delay time which is an important characteristic feature of a delay dynamical system. The procedure is quite robust in the presence of noise.

Suggested Citation

  • Rakshit, Biswambhar & Chowdhury, A. Roy & Saha, Papri, 2007. "Parameter estimation of a delay dynamical system using synchronization in presence of noise," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1278-1284.
    • Handle: RePEc:eee:chsofr:v:32:y:2007:i:4:p:1278-1284
    DOI: 10.1016/j.chaos.2005.12.052
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    Cited by:

    1. Tang, Yinggan & Guan, Xinping, 2009. "Parameter estimation of chaotic system with time-delay: A differential evolution approach," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 3132-3139.
    2. Tarai (Poria), Anindita & Poria, Swarup & Chatterjee, Prasanta, 2009. "Synchronization of bidirectionally coupled chaotic Chen’s system with delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 190-197.
    3. Yang, Xiangfeng & Liu, Yuhan & Park, Gyei-Kark, 2020. "Parameter estimation of uncertain differential equation with application to financial market," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Tang, Yinggan & Cui, Mingyong & Li, Lixiang & Peng, Haipeng & Guan, Xinping, 2009. "Parameter identification of time-delay chaotic system using chaotic ant swarm," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 2097-2102.

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