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Masih Haseli
Masih Haseli
eng.ucsd.edu의 이메일 확인됨 - 홈페이지
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Learning Koopman eigenfunctions and invariant subspaces from data: symmetric subspace decomposition
M Haseli, J Cortés
IEEE Transactions on Automatic Control, 2021
322021
Approximating the Koopman Operator using Noisy Data: Noise-Resilient Extended Dynamic Mode Decomposition
M Haseli, J Cortés
2019 American Control Conference (ACC), 5499-5504, 2019
192019
Parallel learning of Koopman eigenfunctions and invariant subspaces for accurate long-term prediction
M Haseli, J Cortés
IEEE Transactions on Control of Network Systems, 2021
142021
Temporal forward–backward consistency, not residual error, measures the prediction accuracy of extended dynamic mode decomposition
M Haseli, J Cortés
IEEE Control Systems Letters 7, 649-654, 2022
122022
Efficient Identification of Linear Evolutions in Nonlinear Vector Fields: Koopman Invariant Subspaces
M Haseli, J Cortés
IEEE Conference on Decision and Control (CDC), 1746-1751, 2019
122019
Generalizing dynamic mode decomposition: Balancing accuracy and expressiveness in Koopman approximations
M Haseli, J Cortés
Automatica 153, 111001, 2023
112023
Modeling nonlinear control systems via koopman control family: Universal forms and subspace invariance proximity
M Haseli, J Cortés
arXiv preprint arXiv:2307.15368, 2023
92023
Data-driven approximation of Koopman-invariant subspaces with tunable accuracy
M Haseli, J Cortés
2021 American Control Conference (ACC), 470-475, 2021
62021
Fast Identification of Koopman-Invariant Subspaces: Parallel Symmetric Subspace Decomposition
M Haseli, J Cortés
2020 American Control Conference (ACC), 4545-4550, 2020
32020
Invariance proximity: Closed-form error bounds for finite-dimensional koopman-based models
M Haseli, J Cortés
arXiv preprint arXiv:2311.13033, 2023
22023
Data-Driven System Analysis Using the Koopman Operator: Eigenfunctions, Invariant Subspaces, and Accuracy Bounds
M Haseli
University of California, San Diego, 2022
2022
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