Robust Dynamic Mode Decomposition
This paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy-tailed distributions. The proposed RDMD is statist...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9797727/ |
| _version_ | 1811309360302784512 |
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| author | Amir Hossein Abolmasoumi Marcos Netto Lamine Mili |
| author_facet | Amir Hossein Abolmasoumi Marcos Netto Lamine Mili |
| author_sort | Amir Hossein Abolmasoumi |
| collection | DOAJ |
| description | This paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy-tailed distributions. The proposed RDMD is statistically robust because the outliers in the data set are flagged via projection statistics and suppressed using a Schweppe-type Huber generalized maximum-likelihood estimator that minimizes a convex Huber cost function. The latter is solved using the iteratively reweighted least-squares algorithm that is known to exhibit an excellent convergence property and numerical stability than the Newton algorithms. Several numerical simulations using canonical models of dynamical systems demonstrate the excellent performance of the proposed RDMD method. The results reveal that it outperforms several other methods proposed in the literature. |
| first_indexed | 2024-04-13T09:40:51Z |
| format | Article |
| id | doaj.art-53137b7bb8df462392827fe439fb6226 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T09:40:51Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-53137b7bb8df462392827fe439fb62262022-12-22T02:51:55ZengIEEEIEEE Access2169-35362022-01-0110654736548410.1109/ACCESS.2022.31837609797727Robust Dynamic Mode DecompositionAmir Hossein Abolmasoumi0https://orcid.org/0000-0001-9739-1340Marcos Netto1https://orcid.org/0000-0001-7002-3345Lamine Mili2https://orcid.org/0000-0001-6134-3945Electrical Engineering Department, Arak University, Arak, IranPower Systems Engineering Center, NREL, Golden, CO, USABradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Falls Church, VA, USAThis paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy-tailed distributions. The proposed RDMD is statistically robust because the outliers in the data set are flagged via projection statistics and suppressed using a Schweppe-type Huber generalized maximum-likelihood estimator that minimizes a convex Huber cost function. The latter is solved using the iteratively reweighted least-squares algorithm that is known to exhibit an excellent convergence property and numerical stability than the Newton algorithms. Several numerical simulations using canonical models of dynamical systems demonstrate the excellent performance of the proposed RDMD method. The results reveal that it outperforms several other methods proposed in the literature.https://ieeexplore.ieee.org/document/9797727/Dynamic mode decompositionoutlier detectionrobust estimationrobust statisticsrobust regression |
| spellingShingle | Amir Hossein Abolmasoumi Marcos Netto Lamine Mili Robust Dynamic Mode Decomposition IEEE Access Dynamic mode decomposition outlier detection robust estimation robust statistics robust regression |
| title | Robust Dynamic Mode Decomposition |
| title_full | Robust Dynamic Mode Decomposition |
| title_fullStr | Robust Dynamic Mode Decomposition |
| title_full_unstemmed | Robust Dynamic Mode Decomposition |
| title_short | Robust Dynamic Mode Decomposition |
| title_sort | robust dynamic mode decomposition |
| topic | Dynamic mode decomposition outlier detection robust estimation robust statistics robust regression |
| url | https://ieeexplore.ieee.org/document/9797727/ |
| work_keys_str_mv | AT amirhosseinabolmasoumi robustdynamicmodedecomposition AT marcosnetto robustdynamicmodedecomposition AT laminemili robustdynamicmodedecomposition |