<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The time-space fractional-order model (TSFOM) is a generation of the classical diffusion model which is an excellent smoothing method. In this paper, the fractional-order derivative in the model is found to have good performance for peak-preserving. To check the validity and performance of the model, some noisy signals are smoothed by some commonly used smoothing methods and results are compared with those of the proposed model. The comparison result shows that the proposed method outperforms the classical nonlinear diffusion model and some commonly used smoothing methods.</p>
</abstract>

The time-space fractional-order model (TSFOM) is a generation of the classical diffusion model which is an excellent smoothing method. In this paper, the fractional-order derivative in the model is found to have good performance for peak-preserving. To check the validity and performance of the model, some noisy signals are smoothed by some commonly used smoothing methods and results are compared with those of the proposed model. The comparison result shows that the proposed method outperforms the classical nonlinear diffusion model and some commonly used smoothing methods.

Signal Smoothing with Time-Space Fractional Order Model

Nanjing University of Information Science & Technology

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Signal Smoothing with Time-Space Fractional Order Model"}

The time-space fractional-order model (TSFOM) is a generation of the classical diffusion model which is an excellent smoothing method. In this paper, the...

Signal Smoothing with Time-Space Fractional Order Model

Publié en ligne: 30 mars 2021

Pages: 25 - 32

Reçu: 30 sept. 2020

Accepté: 09 févr. 2021

DOI: https://doi.org/10.2478/msr-2021-0004

Mots clés
Fractional diffusion, signal smoothing, filtering

© 2021 Yuanlu Li, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Signal Smoothing with Time-Space Fractional Order Model

Publié en ligne: 30 mars 2021

Pages: 25 - 32

Reçu: 30 sept. 2020

Accepté: 09 févr. 2021

DOI: https://doi.org/10.2478/msr-2021-0004

Mots clésFractional diffusion, signal smoothing, filtering

© 2021 Yuanlu Li, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Fractional diffusion, signal smoothing, filtering