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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.20628 |
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| _version_ | 1866915776937590784 |
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| author | Hansson, Anders da Mata, João Victor Galvão Andersen, Martin S. |
| author_facet | Hansson, Anders da Mata, João Victor Galvão Andersen, Martin S. |
| contents | This paper investigates maximum likelihood estimation for direct system identification in networks of dynamical systems. We establish that the proposed approach is both consistent and efficient. In addition, it is more generally applicable than existing methods, since it can be employed even when measurements are unavailable for all network nodes, provided that network identifiability is satisfied. Finally, we demonstrate that the maximum likelihood problem can be formulated without relying on a predictor, which is key to achieving computationally efficient numerical solutions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_20628 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems Hansson, Anders da Mata, João Victor Galvão Andersen, Martin S. Systems and Control This paper investigates maximum likelihood estimation for direct system identification in networks of dynamical systems. We establish that the proposed approach is both consistent and efficient. In addition, it is more generally applicable than existing methods, since it can be employed even when measurements are unavailable for all network nodes, provided that network identifiability is satisfied. Finally, we demonstrate that the maximum likelihood problem can be formulated without relying on a predictor, which is key to achieving computationally efficient numerical solutions. |
| title | Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2506.20628 |