Fractional order differentiation by integration and error analysis in noisy environment: Part 2 discrete case

In the first part of this work, the differentiation by integration method has been generalized from the integer order to the fractional order so as to estimate the fractional order derivatives of noisy signals. The estimation errors for the proposed fractional order Jacobi differentiators have been studied in continuous case. In this paper, the focus is on the study of these differentiators in discrete case. Firstly, the noise error contribution due to a large class of stochastic processes is studied in discrete case. In particular, it is shown that the differentiator based on the Caputo fractional order derivative can cope with a class of noises, the mean value and variance functions of which are time-variant. Secondly, by using the obtained noise error bound and the error bound for the bias term error obtained in the first part, we analyze the design parameters' influence on the obtained fractional order differentiators. Thirdly, according to the knowledge of the design parameters' influence, the fractional order Jacobi differentiators are significantly improved by admitting a time-delay. In order to reduce the calculation time for on-line applications, a recursive algorithm is proposed. Finally, numerical simulations show their accuracy and robustness with respect to corrupting noises.

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Field Value
Source https://inria.hal.science/hal-00779182
Author Liu, Da-Yan, Gibaru, Olivier, Perruquetti, Wilfrid, Laleg-Kirati, Taous-Meriem
Maintainer CCSD
Last Updated May 15, 2026, 00:56 (UTC)
Created May 15, 2026, 00:56 (UTC)
Identifier hal-00779182
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Estimation Modelling and ANalysis Group (KAUST-CEMSE) ; King Abdullah University of Science and Technology [Thuwal, Saudi Arabia] (KAUST)
creator Liu, Da-Yan
date 2013-01-21T00:00:00
harvest_object_id 6b453d6a-2940-4192-a93b-d881809ad778
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-01-24T00:00:00
set_spec type:UNDEFINED