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Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal
In this paper, a novel form of the Gaussian filter, the Mittag–Leffler filter is presented. This new filter uses the Mittag–Leffler function in the probability-density function. Such Mittag–Leffler distribution is used in the convolution kernel of the filter. The filter has three parameters that may...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694153/ https://www.ncbi.nlm.nih.gov/pubmed/36433336 http://dx.doi.org/10.3390/s22228740 |
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author | Petráš, Ivo |
author_facet | Petráš, Ivo |
author_sort | Petráš, Ivo |
collection | PubMed |
description | In this paper, a novel form of the Gaussian filter, the Mittag–Leffler filter is presented. This new filter uses the Mittag–Leffler function in the probability-density function. Such Mittag–Leffler distribution is used in the convolution kernel of the filter. The filter has three parameters that may adjust the curve shape due to the filter-forgetting factor. Illustrative examples present the main advantages of the proposed filter compared to classical Gaussian filtering techniques, as well as real ECG-signal denoising. Some implementation notes, along with the Matlab function, are also presented. |
format | Online Article Text |
id | pubmed-9694153 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96941532022-11-26 Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal Petráš, Ivo Sensors (Basel) Article In this paper, a novel form of the Gaussian filter, the Mittag–Leffler filter is presented. This new filter uses the Mittag–Leffler function in the probability-density function. Such Mittag–Leffler distribution is used in the convolution kernel of the filter. The filter has three parameters that may adjust the curve shape due to the filter-forgetting factor. Illustrative examples present the main advantages of the proposed filter compared to classical Gaussian filtering techniques, as well as real ECG-signal denoising. Some implementation notes, along with the Matlab function, are also presented. MDPI 2022-11-12 /pmc/articles/PMC9694153/ /pubmed/36433336 http://dx.doi.org/10.3390/s22228740 Text en © 2022 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Petráš, Ivo Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title | Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title_full | Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title_fullStr | Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title_full_unstemmed | Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title_short | Novel Generalized Low-Pass Filter with Adjustable Parameters of Exponential-Type Forgetting and Its Application to ECG Signal |
title_sort | novel generalized low-pass filter with adjustable parameters of exponential-type forgetting and its application to ecg signal |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694153/ https://www.ncbi.nlm.nih.gov/pubmed/36433336 http://dx.doi.org/10.3390/s22228740 |
work_keys_str_mv | AT petrasivo novelgeneralizedlowpassfilterwithadjustableparametersofexponentialtypeforgettinganditsapplicationtoecgsignal |