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PyNumDiff: A Python package for numerical differentiation of noisy time-series data

Detalles Bibliográficos
Autores principales: Van Breugel, Floris, Liu, Yuying, Brunton, Bingni W., Kutz, J. Nathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530632/
https://www.ncbi.nlm.nih.gov/pubmed/37766750
http://dx.doi.org/10.21105/joss.04078
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author Van Breugel, Floris
Liu, Yuying
Brunton, Bingni W.
Kutz, J. Nathan
author_facet Van Breugel, Floris
Liu, Yuying
Brunton, Bingni W.
Kutz, J. Nathan
author_sort Van Breugel, Floris
collection PubMed
description
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spelling pubmed-105306322023-09-27 PyNumDiff: A Python package for numerical differentiation of noisy time-series data Van Breugel, Floris Liu, Yuying Brunton, Bingni W. Kutz, J. Nathan J Open Source Softw Article 2022 2022-03-22 /pmc/articles/PMC10530632/ /pubmed/37766750 http://dx.doi.org/10.21105/joss.04078 Text en https://creativecommons.org/licenses/by/4.0/Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Van Breugel, Floris
Liu, Yuying
Brunton, Bingni W.
Kutz, J. Nathan
PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title_full PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title_fullStr PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title_full_unstemmed PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title_short PyNumDiff: A Python package for numerical differentiation of noisy time-series data
title_sort pynumdiff: a python package for numerical differentiation of noisy time-series data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530632/
https://www.ncbi.nlm.nih.gov/pubmed/37766750
http://dx.doi.org/10.21105/joss.04078
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AT bruntonbingniw pynumdiffapythonpackagefornumericaldifferentiationofnoisytimeseriesdata
AT kutzjnathan pynumdiffapythonpackagefornumericaldifferentiationofnoisytimeseriesdata