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A method for extracting chaotic signal from noisy environment

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  • Shang, Li-Jen
  • Shyu, Kuo-Kai

Abstract

In this paper, we propose a approach for extracting chaos signal from noisy environment where the chaotic signal has been contaminated by white Gaussian noise. The traditional type of independent component analysis (ICA) is capable of separating mixed signals and retrieving them independently; however, the separated signal shows unreal amplitude. The results of this study show with our method the real chaos signal can be effectively recovered.

Suggested Citation

  • Shang, Li-Jen & Shyu, Kuo-Kai, 2009. "A method for extracting chaotic signal from noisy environment," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1120-1125.
  • Handle: RePEc:eee:chsofr:v:42:y:2009:i:2:p:1120-1125
    DOI: 10.1016/j.chaos.2009.03.010
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    References listed on IDEAS

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    Cited by:

    1. Li, Yin & Li, Fagang & Lyu, Shanxiang & Xu, Meng & Wang, Shiyuan, 2021. "Blind extraction of ECG signals based on similarity in the phase space," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    2. Lou, Shuting & Deng, Jiarui & Lyu, Shanxiang, 2022. "Chaotic signal denoising based on simplified convolutional denoising auto-encoder," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).

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