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The influence of noise on nonlinear time series detection based on Volterra–Wiener–Korenberg model

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  • Lei, Min
  • Meng, Guang

Abstract

This paper studies the influence of noises on Volterra–Wiener–Korenberg (VWK) nonlinear test model. Our numerical results reveal that different types of noises lead to different behavior of VWK model detection. For dynamic noise, it is difficult to distinguish chaos from nonchaotic but nonlinear determinism. For time series, measure noise has no impact on chaos determinism detection. This paper also discusses various behavior of VWK model detection with surrogate data for different noises.

Suggested Citation

  • Lei, Min & Meng, Guang, 2008. "The influence of noise on nonlinear time series detection based on Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 36(2), pages 512-516.
    • Handle: RePEc:eee:chsofr:v:36:y:2008:i:2:p:512-516
    DOI: 10.1016/j.chaos.2006.06.084
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    1. Lei, Min & Meng, Guang & Feng, Zhengjin, 2006. "Security analysis of chaotic communication systems based on Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 28(1), pages 264-270.
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    Cited by:

    1. Zhang, Yu & Sprecher, Alicia J. & Zhao, ZongXi & Jiang, Jack J., 2011. "Nonlinear detection of disordered voice productions from short time series based on a Volterra–Wiener–Korenberg model," Chaos, Solitons & Fractals, Elsevier, vol. 44(9), pages 751-758.

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