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Time-fractional diffusion equation for signal smoothing

Author

Listed:
  • Li, Yuanlu
  • Liu, Fawang
  • Turner, Ian W.
  • Li, Tao

Abstract

The time-fractional diffusion equation is used for signal smoothing. Compared to the classical diffusion equation, the time-fractional diffusion equation has another adjustable time-fractional derivative order to control the diffusion process. Therefore, some simulated signals are used to compare the smoothing performance between the time-fractional diffusion equation and the classical diffusion equation as well as between classical smoothing methods (regularization method, Savitzky–Golay method and wavelet method). In the end, the time-fractional diffusion filtering is applied in an NMR spectrum smoothing. Results indicate that the time-fractional diffusion filtering is advantage over the classical diffusion filtering and their smoothing performance is better than that of classical smoothing methods.

Suggested Citation

  • Li, Yuanlu & Liu, Fawang & Turner, Ian W. & Li, Tao, 2018. "Time-fractional diffusion equation for signal smoothing," Applied Mathematics and Computation, Elsevier, vol. 326(C), pages 108-116.
    • Handle: RePEc:eee:apmaco:v:326:y:2018:i:c:p:108-116
    DOI: 10.1016/j.amc.2018.01.007
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    Citations

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    Cited by:

    1. Veeresha, P. & Prakasha, D.G., 2019. "A novel technique for (2+1)-dimensional time-fractional coupled Burgers equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 324-345.
    2. Ansari, Alireza & Derakhshan, Mohammad Hossein, 2024. "Time–space fractional Euler–Poisson–Darboux equation with Bessel fractional derivative in infinite and finite domains," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 218(C), pages 383-402.
    3. Kumar, Yashveer & Singh, Vineet Kumar, 2021. "Computational approach based on wavelets for financial mathematical model governed by distributed order fractional differential equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 531-569.
    4. Derakhshan, Mohammad Hossein & Rezaei, Hamid & Marasi, Hamid Reza, 2023. "An efficient numerical method for the distributed order time-fractional diffusion equation with error analysis and stability," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 214(C), pages 315-333.
    5. Richard L. Magin & Hamid Karani & Shuhong Wang & Yingjie Liang, 2019. "Fractional Order Complexity Model of the Diffusion Signal Decay in MRI," Mathematics, MDPI, vol. 7(4), pages 1-16, April.
    6. Lei Fu & Hongwei Yang, 2019. "An Application of (3+1)-Dimensional Time-Space Fractional ZK Model to Analyze the Complex Dust Acoustic Waves," Complexity, Hindawi, vol. 2019, pages 1-15, August.
    7. Xie, Jiaquan & Wang, Tao & Ren, Zhongkai & Zhang, Jun & Quan, Long, 2019. "Haar wavelet method for approximating the solution of a coupled system of fractional-order integral–differential equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 80-89.
    8. Jian, Huan-Yan & Huang, Ting-Zhu & Ostermann, Alexander & Gu, Xian-Ming & Zhao, Yong-Liang, 2021. "Fast numerical schemes for nonlinear space-fractional multidelay reaction-diffusion equations by implicit integration factor methods," Applied Mathematics and Computation, Elsevier, vol. 408(C).
    9. Samir A. El-Tantawy & Rasool Shah & Albandari W. Alrowaily & Nehad Ali Shah & Jae Dong Chung & Sherif. M. E. Ismaeel, 2023. "A Comparative Study of the Fractional-Order Belousov–Zhabotinsky System," Mathematics, MDPI, vol. 11(7), pages 1-15, April.

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