A local direct method for module identification in dynamic networks with correlated noise KR Ramaswamy, PMJ Van den Hof IEEE Transactions on Automatic Control 66 (11), 5237-5252, 2020 | 58 | 2020 |
Local module identification in dynamic networks using regularized kernel-based methods KR Ramaswamy, G Bottegal, PMJ Van den Hof 2018 IEEE Conference on Decision and Control (CDC), 4713-4718, 2018 | 34 | 2018 |
Learning linear modules in a dynamic network using regularized kernel-based methods KR Ramaswamy, G Bottegal, PMJ Van den Hof Automatica 129, 109591, 2021 | 30 | 2021 |
Local module identification in dynamic networks with correlated noise: the full input case PMJ Van den Hof, KR Ramaswamy, AG Dankers, G Bottegal 58th IEEE Conf. on Decision and Control (CDC), 2019 | 25 | 2019 |
Generalized sensing and actuation schemes for local module identification in dynamic networks KR Ramaswamy, PMJ Van den Hof, AG Dankers 58th IEEE Conf. on Decision and Control (CDC), 2019 | 19 | 2019 |
A frequency domain approach for local module identification in dynamic networks KR Ramaswamy, PZ Csurcsia, J Schoukens, PMJ Van den Hof Automatica 142, 110370, 2022 | 18 | 2022 |
A scalable multi-step least squares method for network identification with unknown disturbance topology SJM Fonken, KR Ramaswamy, PMJ Van den Hof Automatica 141, 110295, 2022 | 18 | 2022 |
Path-based data-informativity conditions for single module identification in dynamic networks PMJ Van den Hof, KR Ramaswamy 2020 59th IEEE Conference on Decision and Control (CDC), 4354-4359, 2020 | 17 | 2020 |
A local direct method for module identification in dynamic networks with correlated noise KR Ramaswamy, PMJ Van den Hof arXiv preprint arXiv:1908.00976, 2019 | 12 | 2019 |
Improved sampling strategies for ensemble-based optimization KR Ramaswamy, RM Fonseca, O Leeuwenburgh, MM Siraj, ... Computational Geosciences 24, 1057-1069, 2020 | 8 | 2020 |
Learning local modules in dynamic networks PMJ Van den Hof, KR Ramaswamy Learning for Dynamics and Control, 176-188, 2021 | 7 | 2021 |
Learning local modules in dynamic networks without prior topology information VC Rajagopal, KR Ramaswamy, PMJ Van den Hof 2021 60th IEEE Conference on Decision and Control (CDC), 840-845, 2021 | 6 | 2021 |
Integrating data-informativity conditions in predictor models for single module identification in dynamic networks PMJ Van den Hof, KR Ramaswamy, SJM Fonken IFAC-PapersOnLine 56 (2), 2377-2382, 2023 | 5 | 2023 |
A regularized kernel-based method for learning a module in a dynamic network with correlated noise VC Rajagopal, KR Ramaswamy, PMJ Van den Hof 2020 59th IEEE Conference on Decision and Control (CDC), 4348-4353, 2020 | 4 | 2020 |
Local identification in dynamic networks using a multi-step least squares method SJM Fonken, KR Ramaswamy, PMJ Van Den Hof 2023 62nd IEEE Conference on Decision and Control (CDC), 431-436, 2023 | 3 | 2023 |
A guide to learning modules in a dynamic network KR Ramaswamy | 3 | 2022 |
A simplified frequency domain approach for local module identification in dynamic networks PZ Csurcsia, K Ramaswamy, J Schoukens, P van den Hof Event29th European Research Network on System Identification Workshop, 2021 | 2 | 2021 |
A local direct method for module identification in dynamic networks with correlated noise. Submitted for publication KR Ramaswamy, PMJ Van den Hof arXiv preprint ArXiv:1908.00976, 2019 | 2 | 2019 |
Learning linear modules in a dynamic network with missing node observations KR Ramaswamy, G Bottegal, PMJ Van den Hof arXiv preprint arXiv:2208.10995, 2022 | 1 | 2022 |
Single module identification in dynamic networks-the current status PMJ Van den Hof, KR Ramaswamy Preprints 21st IFAC World Congress, 52-55, 2020 | 1 | 2020 |