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Model-based adaptive filtering of harmonic perturbations applied to high-frequency noninvasive valvometry
Abstract : In this paper, a model-based adaptive filter is used to suppress electrical noise in a high-frequency noninvasive valvometry device, which is part of an autonomous biosensor system using bivalve mollusks valve-activity measurements for ecological monitoring purposes. The proposed model-based adaptive filter uses the dynamic regressor extension and mixing method to allow a decoupled estimation of the parameters. Once the desired regression form of the output model is obtained, a fixed-time estimation approach is used to identify its parameters. By applying these two techniques, a flexible filter structure is obtained with the property of retaining the major relevant components of interest of the original valve-activity signals, even in the case when the unwanted signal frequency components are in the same frequency range as the useful variables.
Cited literature [11 references]
https://hal.inria.fr/hal-02887927
Contributor : Rosane Ushirobira <>
Submitted on : Thursday, July 2, 2020 - 3:52:10 PM
Last modification on : Friday, December 11, 2020 - 6:44:08 PM
Long-term archiving on: : Thursday, September 24, 2020 - 5:18:49 AM
Contributor : Rosane Ushirobira <>
Submitted on : Thursday, July 2, 2020 - 3:52:10 PM
Last modification on : Friday, December 11, 2020 - 6:44:08 PM
Long-term archiving on: : Thursday, September 24, 2020 - 5:18:49 AM
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BUESM_IFAC_2020.pdf
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