Deep Koopman Learning using Noisy Data Article Swipe
Wenjian Hao
,
Devesh Upadhyay
,
Shaoshuai Mou
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2405.16649
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2405.16649
This paper proposes a data-driven framework to learn a finite-dimensional approximation of a Koopman operator for approximating the state evolution of a dynamical system under noisy observations. To this end, our proposed solution has two main advantages. First, the proposed method only requires the measurement noise to be bounded. Second, the proposed method modifies the existing deep Koopman operator formulations by characterizing the effect of the measurement noise on the Koopman operator learning and then mitigating it by updating the tunable parameter of the observable functions of the Koopman operator, making it easy to implement. The performance of the proposed method is demonstrated on several standard benchmarks. We then compare the presented method with similar methods proposed in the latest literature on Koopman learning.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2405.16649
- https://arxiv.org/pdf/2405.16649
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
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- DOI
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https://doi.org/10.48550/arxiv.2405.16649Digital Object Identifier
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Deep Koopman Learning using Noisy DataWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-05-26Full publication date if available
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Wenjian Hao, Devesh Upadhyay, Shaoshuai MouList of authors in order
- Landing page
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https://arxiv.org/abs/2405.16649Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2405.16649Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2405.16649Direct OA link when available
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Deep learning, Artificial intelligence, Computer science, Econometrics, MathematicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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