Searched for: %2520
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van Haren, Max (author), Blanken, Lennart (author), Oomen, T.A.E. (author)
Frequency-domain representations of multirate systems are essential for controller design and performance evaluation of multirate systems and sampled-data control. The aim of this paper is to develop a time-efficient closed-loop identification approach for multirate systems in the frequency-domain. The developed method utilizes local polynomial...
conference paper 2022
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Bos, F.R.R.C. (author), Anil Meera, A. (author), Benders, D. (author), Wisse, M. (author)
The free energy principle from neuroscience provides a brain-inspired perception scheme through a data-driven model learning algorithm called Dynamic Expectation Maximization (DEM). This paper aims at introducing an exper-imental design to provide the first experimental confirmation of the usefulness of DEM as a state and input estimator for...
conference paper 2022
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Fioranelli, F. (author), Zhu, S. (author), Roldan Montero, I. (author)
Linked to the increasing availability of datasets for radar-based human activity recognition (HAR), in this Student Highlights contribution, we report on a classification project that a group of 23 graduate students performed at TU Delft. The students were asked to work in groups of 2-3 members and to use the publicly available University of...
journal article 2022
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Zhang, Rongkai (author), Zhu, Jiang (author), Zha, Zhiyuan (author), Dauwels, J.H.G. (author), Wen, Bihan (author)
State-of-the-art image denoisers exploit various types of deep neural networks via deterministic training. Alternatively, very recent works utilize deep reinforcement learning for restoring images with diverse or unknown corruptions. Though deep reinforcement learning can generate effective policy networks for operator selection or architecture...
conference paper 2021
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Patel, Abhilash (author), Roy, Spandan (author), Baldi, S. (author)
By increasingly relying on network-based operation for control, monitoring, and protection functionalities, modern wide-area power systems have also become vulnerable to cyber-attacks aiming to damage system performance and/or stability. Resilience in state-of-the-art methods mostly relies on known characteristics of the attacks and static...
journal article 2021
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Liu, Di (author), Baldi, S. (author), Jain, V. (author), Yu, Wenwu (author), Frasca, Paolo (author)
Recently proposed adaptive platooning strategies for connected automated vehicles are able to cope with uncertain vehicle parameters (uncertain driveline time constants), but can handle only acyclic graphs like look-ahead graphs. This prevents from enhancing platooning protocols with synchronized merging maneuvers, where cyclic communication...
journal article 2021
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Xia, Z. (author), Booij, Olaf (author), Manfredi, Marco (author), Kooij, J.F.P. (author)
Cross-view matching aims to learn a shared image representation between ground-level images and satellite or aerial images at the same locations. In robotic vehicles, matching a camera image to a database of geo-referenced aerial imagery can serve as a method for self-localization. However, existing work on cross-view matching only aims at...
journal article 2021
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Mohammadi, Majid (author), Hofman, Wout (author), Tan, Y. (author)
Comparing ontology matching systems are typically performed by comparing their average performances over multiple datasets. However, this paper examines the alignment systems using statistical inference since averaging is statistically unsafe and inappropriate. The statistical tests for comparison of two or multiple alignment systems are...
journal article 2018
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Meijer, Jonathan (author), Lei, Q. (author), Wisse, M. (author)
This paper identifies high-performing Open Motion Planning Library (OMPL) planners for grasp execution and simultaneously presents useful benchmark data. Four grasp executions were defined using a UR5 manipulator. The performance was measured by means of solved runs, computing time and path length. Based on the results, planners are...
conference paper 2017
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Pool, E.A.I. (author), Kooij, J.F.P. (author), Gavrila, D. (author)
We learn motion models for cyclist path prediction on real-world tracks obtained from a moving vehicle, and propose to exploit the local road topology to obtain better predictive distributions. The tracks are extracted from the Tsinghua-Daimler Cyclist Benchmark for cyclist detection, and corrected for vehicle egomotion. Tracks are then...
conference paper 2017
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