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Signal Smoothing with Time-Space Fractional Order Model Cover

Signal Smoothing with Time-Space Fractional Order Model

By: Yuanlu Li  
Open Access
|Mar 2021

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.

Language: English
Page range: 25 - 32
Submitted on: Sep 30, 2020
Accepted on: Feb 9, 2021
Published on: Mar 30, 2021
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2021 Yuanlu Li, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.