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Yuji Saito
Yuji Saito
Frontier Research Institute for Interdisciplinary Sciences, Tohoku University
Bestätigte E-Mail-Adresse bei tohoku.ac.jp - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Mission to earth–moon lagrange point by a 6u cubesat: Equuleus
R Funase, S Ikari, K Miyoshi, Y Kawabata, S Nakajima, S Nomura, ...
IEEE Aerospace and Electronic Systems Magazine 35 (3), 30-44, 2020
652020
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
622021
Verification firings of end-burning type hybrid rockets
H Nagata, H Teraki, Y Saito, R Kanai, H Yasukochi, M Wakita, T Totani
Journal of propulsion and power 33 (6), 1473-1477, 2017
502017
Fuel regression characteristics of a novel axial-injection end-burning hybrid rocket
Y Saito, T Yokoi, H Yasukochi, K Soeda, T Totani, M Wakita, H Nagata
Journal of Propulsion and Power 34 (1), 247-259, 2018
46*2018
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
392021
Method for determining nozzle-throat-erosion history in hybrid rockets
L Kamps, Y Saito, R Kawabata, M Wakita, T Totani, Y Takahashi, ...
Journal of propulsion and power 33 (6), 1369-1377, 2017
372017
Data-driven Vector-measurement-sensor Selection based on Greedy Algorithm
Y Saito, T Nonomura, K Nankai, K Yamada, K Asai, Y Tsubakino, ...
IEEE Sensors Letters 4, 2020
332020
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
312021
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
302021
Investigation of graphite nozzle erosion in hybrid rockets using oxygen/high-density polyethylene
L Kamps, S Hirai, K Sakurai, T Viscor, Y Saito, R Guan, H Isochi, N Adachi, ...
Journal of propulsion and power 36 (3), 423-434, 2020
30*2020
High pressure fuel regression characteristics of axial-injection end-burning hybrid rockets
Y Saito, M Kimino, A Tsuji, Y Okutani, K Soeda, H Nagata
Journal of Propulsion and Power 35 (2), 328-341, 2019
28*2019
Feasibility study on real-time observation of flow velocity field using sparse processing particle image velocimetry
N Kanda, K Nakai, Y Saito, T Nonomura, K Asai
Transactions of the Japan Society for Aeronautical and Space Sciences 64 (4 …, 2021
242021
Comprehensive Data Reduction for N2O/HDPE Hybrid Rocket Motor Performance Evaluation
L Kamps, K Sakurai, Y Saito, H Nagata
Aerospace 6 (4), 45, 2019
242019
Randomized subspace newton convex method applied to data-driven sensor selection problem
T Nonomura, S Ono, K Nakai, Y Saito
IEEE Signal Processing Letters 28, 284-288, 2021
222021
The accuracy of reconstruction techniques for determining hybrid rocket fuel regression rate
Y Saito, LT Kamps, K Komizu, D Bianchi, F Nasuti, H Nagata
2018 Joint Propulsion Conference, 4923, 2018
202018
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
182021
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
162022
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
16*2022
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
152022
Optimization of sparse sensor placement for estimation of wind direction and surface pressure distribution using time-averaged pressure-sensitive paint data on automobile model
R Inoba, K Uchida, Y Iwasaki, T Nagata, Y Ozawa, Y Saito, T Nonomura, ...
Journal of Wind Engineering and Industrial Aerodynamics 227, 105043, 2022
152022
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