Antonio (2026). FIF2 (https://github.com/Acicone/FIF2/releases/tag/v3.0.1), GitHub.
Recuperato .
Cicone, Antonio, and Haomin Zhou. “Multidimensional Iterative Filtering Method for the Decomposition of High–Dimensional Non–Stationary Signals.” Numerical Mathematics: Theory, Methods and Applications, vol. 10, no. 2, Global Science Press, May 2017, pp. 278–98, doi:10.4208/nmtma.2017.s05.
Cicone, Antonio, and Haomin Zhou. “Multidimensional Iterative Filtering Method for the Decomposition of High–Dimensional Non–Stationary Signals.” Numerical Mathematics: Theory, Methods and Applications, vol. 10, no. 2, Global Science Press, May 2017, pp. 278–98, doi:10.4208/nmtma.2017.s05.
APA
Cicone, A., & Zhou, H. (2017). Multidimensional Iterative Filtering Method for the Decomposition of High–Dimensional Non–Stationary Signals. Numerical Mathematics: Theory, Methods and Applications, 10(2), 278–298. Global Science Press. Retrieved from https://doi.org/10.4208%2Fnmtma.2017.s05
BibTeX
@article{Cicone_2017,
doi = {10.4208/nmtma.2017.s05},
url = {https://doi.org/10.4208%2Fnmtma.2017.s05},
year = 2017,
month = {may},
publisher = {Global Science Press},
volume = {10},
number = {2},
pages = {278--298},
author = {Antonio Cicone and Haomin Zhou},
title = {Multidimensional Iterative Filtering Method for the Decomposition of High{\textendash}Dimensional Non{\textendash}Stationary Signals},
journal = {Numerical Mathematics: Theory, Methods and Applications}
}
Cicone, Antonio, and Haomin Zhou. “Numerical Analysis for Iterative Filtering with New Efficient Implementations Based on FFT.” Numerische Mathematik, vol. 147, no. 1, Springer Science and Business Media LLC, Jan. 2021, pp. 1–28, doi:10.1007/s00211-020-01165-5.
Cicone, Antonio, and Haomin Zhou. “Numerical Analysis for Iterative Filtering with New Efficient Implementations Based on FFT.” Numerische Mathematik, vol. 147, no. 1, Springer Science and Business Media LLC, Jan. 2021, pp. 1–28, doi:10.1007/s00211-020-01165-5.
APA
Cicone, A., & Zhou, H. (2021). Numerical analysis for iterative filtering with new efficient implementations based on FFT. Numerische Mathematik, 147(1), 1–28. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs00211-020-01165-5
BibTeX
@article{Cicone_2021,
doi = {10.1007/s00211-020-01165-5},
url = {https://doi.org/10.1007%2Fs00211-020-01165-5},
year = 2021,
month = {jan},
publisher = {Springer Science and Business Media {LLC}},
volume = {147},
number = {1},
pages = {1--28},
author = {Antonio Cicone and Haomin Zhou},
title = {Numerical analysis for iterative filtering with new efficient implementations based on {FFT}},
journal = {Numerische Mathematik}
}
Stallone, Angela, et al. “New Insights and Best Practices for the Successful Use of Empirical Mode Decomposition, Iterative Filtering and Derived Algorithms.” Scientific Reports, vol. 10, no. 1, Springer Science and Business Media LLC, Sept. 2020, doi:10.1038/s41598-020-72193-2.
Stallone, Angela, et al. “New Insights and Best Practices for the Successful Use of Empirical Mode Decomposition, Iterative Filtering and Derived Algorithms.” Scientific Reports, vol. 10, no. 1, Springer Science and Business Media LLC, Sept. 2020, doi:10.1038/s41598-020-72193-2.
APA
Stallone, A., Cicone, A., & Materassi, M. (2020). New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms. Scientific Reports, 10(1). Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1038%2Fs41598-020-72193-2
BibTeX
@article{Stallone_2020,
doi = {10.1038/s41598-020-72193-2},
url = {https://doi.org/10.1038%2Fs41598-020-72193-2},
year = 2020,
month = {sep},
publisher = {Springer Science and Business Media {LLC}},
volume = {10},
number = {1},
author = {Angela Stallone and Antonio Cicone and Massimo Materassi},
title = {New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms},
journal = {Scientific Reports}
}
S. Sfarra, A. Cicone, B. Yousefi, S. Perilli, L. Robol, X. P.V. Maldague. "Maximizing the detection of thermal imprints in civil engineering composites after a thermal stimulus - The contribution of an innovative mathematical pre-processing tool: the 2D Fast Iterative Filtering algorithm. Philosophy, comparisons, numerical, qualitative and quantitative results". 2021. Submitted
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
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