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Yamada Keigo
Yamada Keigo
Tohoku Univ., Japan
Bestätigte E-Mail-Adresse bei dc.tohoku.ac.jp
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Zitiert von
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Jahr
Determinant-based fast greedy sensor selection algorithm
Y Saito, T Nonomura, K Yamada, K Nakai, T Nagata, K Asai, Y Sasaki, ...
IEEE Access 9, 68535-68551, 2021
722021
Fast greedy optimization of sensor selection in measurement with correlated noise
K Yamada, Y Saito, K Nankai, T Nonomura, K Asai, D Tsubakino
Mechanical Systems and Signal Processing 158, 107619, 2021
492021
Data-driven sparse sensor selection based on A-optimal design of experiment with ADMM
T Nagata, T Nonomura, K Nakai, K Yamada, Y Saito, S Ono
IEEE Sensors Journal 21 (13), 15248-15257, 2021
392021
Data-driven vector-measurement-sensor selection based on greedy algorithm
Y Saito, T Nonomura, K Nankai, K Yamada, K Asai, Y Sasaki, ...
IEEE Sensors Letters 4 (7), 1-4, 2020
362020
Effect of objective function on data-driven greedy sparse sensor optimization
K Nakai, K Yamada, T Nagata, Y Saito, T Nonomura
IEEE Access 9, 46731-46743, 2021
352021
Seismic wavefield reconstruction based on compressed sensing using data-driven reduced-order model
T Nagata, K Nakai, K Yamada, Y Saito, T Nonomura, M Kano, S Ito, ...
Geophysical Journal International 233 (1), 33-50, 2023
222023
Data-driven sensor selection method based on proximal optimization for high-dimensional data with correlated measurement noise
T Nagata, K Yamada, T Nonomura, K Nakai, Y Saito, S Ono
IEEE Transactions on Signal Processing 70, 5251-5264, 2022
202022
Data-Driven Determinant-Based Greedy Under/Oversampling Vector Sensor Placement.
Y Saito, K Yamada, N Kanda, K Nakai, T Nagata, T Nonomura, K Asai
CMES-Computer Modeling in Engineering & Sciences 129 (1), 2021
202021
Nondominated-solution-based multi-objective greedy sensor selection for optimal design of experiments
K Nakai, Y Sasaki, T Nagata, K Yamada, Y Saito, T Nonomura
IEEE Transactions on Signal Processing 70, 5694-5707, 2022
192022
Greedy sensor selection for weighted linear least squares estimation under correlated noise
K Yamada, Y Saito, T Nonomura, K Asai
IEEE Access 10, 79356-79364, 2022
19*2022
Randomized group-greedy method for large-scale sensor selection problems
T Nagata, K Yamada, K Nakai, Y Saito, T Nonomura
IEEE Sensors Journal 23 (9), 9536-9548, 2023
182023
Proof-of-concept study of sparse processing particle image velocimetry for real time flow observation
N Kanda, C Abe, S Goto, K Yamada, K Nakai, Y Saito, K Asai, ...
Experiments in Fluids 63 (9), 143, 2022
182022
Sensor selection by greedy method for linear dynamical systems: Comparative study on Fisher-information-matrix, observability-Gramian and Kalman-filter-based indices
S Takahashi, Y Sasaki, T Nagata, K Yamada, K Nakai, Y Saito, ...
IEEE Access, 2023
92023
Observation site selection for physical model parameter estimation towards process-driven seismic wavefield reconstruction
K Nakai, T Nagata, K Yamada, Y Saito, T Nonomura, M Kano, S Ito, ...
Geophysical Journal International 234 (3), 1786-1805, 2023
82023
Efficient sensor node selection for observability Gramian optimization
K Yamada, Y Sasaki, T Nagata, K Nakai, D Tsubakino, T Nonomura
Sensors 23 (13), 5961, 2023
72023
Sensor Selection with Cost Function using Nondominated-Solution-based Multi-objective Greedy Method
Y Saito, K Nakai, T Nagata, K Yamada, T Nonomura, K Sakaki, Y Nunome
IEEE Sensors Journal, 2023
42023
Assessment of Sensor Optimization Methods Toward State Estimation in a High-Dimensional System using Kalman Filter
T Nagata, Y Sasaki, K Yamada, M Watanabe, D Tsubakino, T Nonomura
IEEE Sensors Journal, 2024
22024
Improved estimation of yaw angle and surface pressure distribution of Ahmed model with optimized sparse sensors by Bayesian framework based on pressure-sensitive paint data
R Inoba, K Uchida, Y Iwasaki, K Yamada, A Jebli, T Nagata, Y Ozawa, ...
Experimental Thermal and Fluid Science 156, 111210, 2024
12024
Fast data-driven greedy sensor selection for ridge regression
Y Sasaki, K Yamada, T Nagata, Y Saito, T Nonomura
arXiv preprint arXiv:2402.10596, 2024
12024
Determinant factors of performance in token test for japanese aphasics
K Yamada
International Journal of Psychology 27 (3-4), 393-393, 1992
11992
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